Advanced Stats Helping Explain The Way Things Are
So a couple of days ago if you read the From The Branches, or if you keep tabs on what Gabe Desjardins is up to at BehindTheNet.ca (or Arctic Ice Hockey), you may have noticed that the Fenwick Percentages for the 2011-12 season were added to the mix of advanced stats that are maintained on his site.
This is great news for those of you that are interested in explanations of what they've seen so far this young NHL season. People like numbers when they can summarize things quickly. It helps when they know what the heck they mean, but being able to compare teams quickly and accurately in a fashion that's meaningful is really what makes things in sports stats worthwhile (in my opinion).
We've obviously got the point system for that as far as the standings go, but the problem with using points and standings is that we don't have an easy way to account for strength of schedule, competition, good or bad refereeing, luck, etc. It's hard to figure out half way though the year which teams are good, and which teams are just lucky.
Knowing this, we look for ways to compare teams. Well, we can compare how well their goalies are playing, but that doesn't mean much for the skaters. We can tell who is putting up more goals, and letting more go in, but again, we know in the short term that a lot of that variation is largely due to luck. So what can we follow that is repeatable, consistent, and will have an impact over the long term?
In sports like football (all versions of it - Canadian, American, European, Rugby, etc.) the key stat for most astute observers would be possession. Teams that control the ball tend to control the play, and thus are usually more likely to win. They don't ALWAYS win, but they tend to. Unfortunately, the NHL doesn't keep or produce regular possession statistics. Even if they did, we'd be relying on score keepers to track things like giveaways, takeaways and the like, and there's issues with that - generally we'd like to avoid those as much as possible.
So what proxies do we have for possession in hockey? Well, generally the team that has the puck more in the oppositions end, is likely to have more opportunities to attempt to score... that is to say, fire shots in the direction of their opposition's net. Not all shots will make it to their target. Many miss, and some are blocked and the majority are actually stopped by the goalie. But what we can do is compare the number of attempts for each team on the ice, and use this comparison as an effort to determine who is controlling play more frequently.
Two numbers exist for this purpose. The first, devised by Buffalo goalie coach Jim Corsi and given the same name (Corsi Number) is simply a plus / minus statistic that adds up all of the shot attempts for a team (SOG, MSF, and BSA) and subtracts all the shot attempts they surrender (SOG, MSA, BSF). It's simple, and easy to observe, but the point has been raised that blocked shots are rarely a favourable outcome of any sort, and including them may or may not cloud the picture.
As a result of this argument, Calgary Flames blogger Matt Fenwick proposed the removal of blocked shots from the assessment. The resulting value which is the plus / minus of shot attempts (those on target and those that miss) for the team and against them, is termed the Fenwick number. A Fenwick Event is considered any shot attempt that hits the net or misses it, but is not blocked.
For the sake of easy comparison, Fenwick Events can be used in a number form (like Corsi) and provided on a per 60 minute basis, or as has been more recently suggested, presented as a percentage. If you assign all Fenwick Events to the home and away team, each team will have a percentage of the total number of events in any given game. Similarly, if you add up all the Fenwick Events in favour of a given team over the course of their season, and divide them by the total number of events in the games they play in, you would determine a Fenwick Events Percentage on a seasonal basis. This is something you can easily compare; it's ONE number.
Ok so now we know a decent number that we can use as a reasonable proxy for possession, but there are some other issues to take into consideration. 1) Score effects: when the a team trails it tends to work harder to play catch up vs. the opposition, and when they are in the lead they tend to sit back and protect the lead. This skews Fenwick and Corsi numbers quite drastically. 2) Scorers in different stadiums tend to award Fenwick Events at different rates. Shots and Missed Shots vary quite a bit from stadium to stadium, and this inconsistency is difficult to deal with, particularly when a team's home scorer skews things drastically one way or another.
In an effort to compensate for these two problems by looking at the Fenwick Event Percentages when the score is tied (nobody is playing catch up or sitting back), and when a team plays on the road (their home scorer's bias won't show up in the data).
So here's a number we can put some faith in over the longer haul of a season to compare teams with: Road Fenwick Percentage When Tied. So how does that shake out so far in the season? Here's a look at things as of November 23rd (I don't believe the data will include tonight's games though). I've also included PDO to give you a quick read on the type of "puck luck" the team has had at even strength so far this year (remember that teams tend to regress towards scores of 1000 as the season progresses).
| Team | Road Fenwick % (TIED) | PDO | Record |
| CHI | 55.47 | 996 | 12-6-3 |
| PIT | 55.25 | 992 | 12-6-4 |
| PHX | 54.44 | 1016 | 11-6-3 |
| FLA | 54.39 | 1012 | 12-6-3 |
| SJS | 53.13 | 1022 | 12-5-1 |
| STL | 52.89 | 1015 | 11-8-2 |
| DET | 51.82 | 1010 | 12-7-1 |
| COL | 51.60 | 961 | 9-11-1 |
| WSH | 50.20 | 1006 | 12-7-1 |
| OTT | 50.00 | 976 | 10-9-2 |
| TOR | 49.77 | 1003 | 12-8-2 |
| LAK | 49.10 | 997 | 11-7-4 |
| MTL | 48.97 | 1001 | 10-9-3 |
| CBJ | 48.26 | 973 | 5-13-3 |
| NJD | 48.06 | 978 | 11-8-1 |
| WPG | 48.00 | 992 | 8-9-4 |
| VAN | 47.55 | 975 | 10-9-1 |
| DAL | 46.72 | 1005 | 13-8-0 |
| BUF | 46.30 | 1007 | 12-8-1 |
| NYI | 45.97 | 964 | 5-10-4 |
| PHI | 45.45 | 1009 | 12-6-3 |
| EDM | 44.95 | 1013 | 11-8-2 |
| NYR | 44.27 | 1042 | 10-5-3 |
| NSH | 44.26 | 1022 | 10-7-4 |
| CAR | 43.36 | 987 | 8-11-4 |
| BOS | 43.33 | 1034 | 13-7-0 |
| ANA | 41.27 | 979 | 6-11-4 |
| CGY | 38.24 | 999 | 8-11-1 |
| TBL | 38.22 | 994 | 9-9-2 |
| MIN | 34.57 | 1033 | 13-5-3 |
So what does this tell us? Well I think it's clear that Minnesota probably isn't the best team in the NHL, despite being 1st overall right now. Their goaltending has carried them so far, and the likelihood of it lasting all year is far from high. The same could be said of Boston, whose recent 10 game winning streak has been piled upon a pile of backup goalies subbing for injured starters, and teams in the midst of scoring problems. It also helps that they have Tim Thomas and Rask in goal, but I think by now we can admit that for them .930+ goaltending is "sustainable".
At the other end of the spectrum we have Colorado getting seriously jobbed right now by some horrid luck. Largely this stems from their crappy shooting percentage. They get a lot of shots on goal, and eventually they'll start going in. Similarly, though to a lesser extent, this could be said for Ottawa, New Jersey, Columbus, and Vancouver. Unfortunately for Devils' fans I don't know if they should expect serious offense or drastically improved goaltending anytime soon though.
Ottawa's goaltending carousel isn't settled, Columbus needs to ride out this stormy early part of the season, and Vancouver is hoping Luongo can sort his game out sooner rather than later.
All of the teams with Road Fenwick % While Tied over 50%, that have a PDO close to 1000 are sitting fairly pretty as their season isn't likely to shift suddenly, and they're playing well over the first 20ish games. This bodes well for Chicago, Pittsburgh, Washington, and to a lesser extent Toronto. The first 3 are relatively legit contenders whose records are unlikely to fall out of playoff contention.
Toronto's numbers indicate that their early season burst isn't really a mirage. They're not outperforming anything in particular. Yes they're scoring a lot but their goal tending has been bad, and odds are when one gets worse, the other will improve. Their is room to improve on the Fenwick front, but the team does look close to turning a corner towards being competitive.
Unfortunate reality needs to set in for Calgary and Tampa Bay. Neither team is particularly productive in terms of controlling play offensively and they give up far too much. Their PDO values also indicate that they aren't likely to change much going forward. These are teams that likely need to make trades if they hope to have a shot at the post season.
Let me know if you have any questions and feel free to debate the worth or value of the stat - I know some of you want to.
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what? no graphs?
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 10:05 AM EST reply actions
At least give me a picture of something!
The Leafs are my Rushmore
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I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 10:10 AM EST up reply actions
PPP’s got us covered. He knows how to keep us quiet in the back seat.
by Spezzal Teams Playa on Nov 25, 2011 2:25 AM EST up reply actions
I spoiled you guys in the summer, now you demand them all the time
No more moral victories, no more excuses. Put up or shut up.
Lebda-free since July 3.
by nhlcheapshot on Nov 24, 2011 11:32 AM EST up reply actions
Why would that trend back to 1000 though? If I’ve got Tim Thomas, Sidney Crosby, Ovechkin, Kessel, and Phaneuf playing for me I SHOULD have a save % + shooting % that’s considerably better than league average.
I tried making that argument a while back. There isn’t a reason it should trend to 1000 on a team. In the league, it obviously does, but there’s no intrinsic reason why it should on the team level. It’s like saying that if you flip a coin a thousand times, it will trend towards a 50/50 split between heads and tails. What actually happens is that the results are likely to fall somewhere in the 60/40 40/60 range (not exactly but close) thanks to the different possible permutations.
Come get your duds in order...
On the league level it is mathematically forced to add up to 100%, because every shot that goes in adds to shooting percent, and takes from save percent, and vice versa.
But on a league wide level the total +/- stat must ALSO add to zero (at even strength, for every player on the ice when there was a goal scored for, there was also a player on the ice that was scored against), but we don’t expect THAT to regress back to zero for every player, and we don’t regard it as a signal of unsustainable luck when a player has a particularly high or low one.
But on a league wide level the total +/- stat must ALSO add to zero (at even strength, for every player on the ice when there was a goal scored for, there was also a player on the ice that was scored against),
This is actually incorrect because it ignores the effect of short-handed goals, where fewer players get credited with a Plus than do a Minus
Cynically Sarcastic
Сертыфікаваны Grabbo Палюбоўнік
Was just about to say this… happens in almost every EN situation
No more moral victories, no more excuses. Put up or shut up.
Lebda-free since July 3.
by nhlcheapshot on Nov 24, 2011 12:18 PM EST up reply actions
PP’s don’t count for +/- is my understanding.
Perhaps a few empty net goals would throw the total off EXACTLY 0, but it’d still be something like .002 for the whole league.
Yeah but there aren’t teams with 4 lines consisting of Crosby, Ovechkin, Kessel, and Phaneuf, etc. And even those beasts can’t play 60 minutes a night. I think it’s fair to say that even for teams with very good players, the PDO should end up at some number that’s close to 1000.
For what it’s worth, the 4 2011-2012 All-Stars (including 2 2011-2012 Stanley Cup Champions) you listed play on teams with PDOs near 1000.
by stevesmith19 on Nov 24, 2011 12:13 PM EST up reply actions
That’s a contingent argument, and only says that given the way teams are built now, we should expect PDO to fall roughly around 1000. That’s not an argument for why the stat necessarily trends towards 1000.
Come get your duds in order...
The data has been run on the individual player level, and while a small number of players are able to put up better than 1000 or worse than 1000 on account of skill, it’s not true of most players. Someone (I think it was mc79) did a post comparing the players with the best and worst PDOs at the half-way mark of the season one year, and I believe every single one of them ended up closer to 1000 by the end of the year.
I don’t think anyone believes that all teams or players will necessarily end up with a PDO of 1000, just that over a large enough sample it tends to.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 12:36 PM EST up reply actions
Here we go, mc79 has a post about it on the team level. You’ll note that of the 20 best and 20 worst PDO teams from 2003-04 to 2007-08, only 3 failed to see their PDO numbers regress after the first quarter of the season.
http://www.mc79hockey.com/?p=2996
I know he’s done it with individual players too, but I can’t find the post now.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 12:41 PM EST up reply actions
But that’s what regression to the mean IS.
If you picked the top and bottom 3 goal scorers in the league in any given half of the season they would ALSO regress back to the mean.
The question isn’t whether statistically extreme scores will tend to drop – they will. It’s whether some teams are consistently above or below 1. I would be shocked if the Boston Bruins at the end of last year didn’t have a higher PDO than th elast place team. They had a better goalie with a higher save percent, and they have more talented forwards.
The only reason you’d expect them to regress back to 1 is that there’s very little variance between goalies in save percent (given 100 shots on an elite goalie and on a scrub, they would produce the exact same result on 97 of those shots – think about that), and the variance between players seems to be far more in their shot rates than in their shooting percentages.
Putting it this way, I guess the justification for the statistic is that the underlying numbers its based on have a very high ratio of luck to skill in them, but an oversized impact on the outcome of games. Hmmm.
Well I guess we answered the question after all.
Ok, but then we have to acknowledge that a PDO of 1000 has no special value. There’s no actual reason that players should see their PDO shift towards 1000, it’s just that most players tend to have numbers end up roughly around 1000.
Come get your duds in order...
There is a reason, and that reason is luck (or chance or natural variation or whatever else you want to call it). If you don’t believe that’s what the effect is, you’re welcome to come up with alternate explanations.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 1:02 PM EST up reply actions
If most NHL players are on average equivalent in skill, then luck would be 50/50 and over the season PDO would migrate to a natural level of 1000 in a large enough sample size. Now if it was Team Lebda +Toskala versus Team Crosby + Thomas well PDO would be skewed.
How would PDO be affected by conjoined twins playing on different teams?
Paedophiles are using an area of internet the size of Ireland.
should clarify this
PDO is Even Strength TM SH% + SV%.
Few players with high SH% actually elevate it a lot at ES. They often bump it up on the PP when better scoring chances present themselves. Similarly SV% suffers on the PK so we go back to ES SV% because it’s less randomly variable due to small sample sizes.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 6:05 PM EST via mobile up reply actions
I believe its on ice.
About time that people finally realized how awesome Gunnar is...
Certified Gunnar & Kule lover!
My new goal: To get the nickname Hebrew Hammer for Mike Brown to take off.
"On Ice"
Is irrelevant when discussing team percentages. There’s no “off ice” scoring at the team level.
You are correct w.r.t. Individual players though.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 6:07 PM EST via mobile up reply actions
Looking at Road Fenwick% + PDO is a great idea. If any of the scoring chance posse is reading this, we should add in SC% as well.
"Shots aren't the important thing. Scoring chances are way more important than shots." - Bruce Boudreau
See my work in the Washington Post and on ESPN Insider.
Follow me on Twitter @ngreenberg
One thing that I wonder about here is the fact that only 10/30 teams have a Fenwick% over 50, with no one over 55 but 3 teams under 40. Shouldn’t the average fall somewhere near 50, or are home teams really that dominant in terms of Fenwick? Is this possibly a sample size issue because we’re still early in the season?
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
Pretty big splits between home and road Fenwick over the course of the season. I’m not sure how much of that is luck and how much of that is coaches getting favorable matchups at home.
"Essentially, all models are wrong, but some are useful" George E.P. Box
I have $50 to Olie's autism charity or So Kids Can and a beer on the under for 50/57/107 as AO's final stat line for 2011-'12
And on Pekka Rinne's PK SV% dropping under .920 by the end of the '12 season
by Knee high to a duck on Nov 24, 2011 10:22 AM EST up reply actions
Something that points to coaches getting matchups at home versus on the road – Vancouver matches aggressively to zone starts instead of opposition (take a look at their Corsi Rel QoC spread from last year, it’s very small from top-to-bottom) and their Road and Home Fenwick scores are almost identical.
Again though, how much of that is luck and how much of that is the Vancouver official scorer isn’t something I know how to tease out with the data set that I have.
"Essentially, all models are wrong, but some are useful" George E.P. Box
I have $50 to Olie's autism charity or So Kids Can and a beer on the under for 50/57/107 as AO's final stat line for 2011-'12
And on Pekka Rinne's PK SV% dropping under .920 by the end of the '12 season
by Knee high to a duck on Nov 24, 2011 10:25 AM EST up reply actions
So I have a bit of a concern re. interpretation of these numbers.
The title of the post is suggests that Fenwick (or Road Fenwick%) is meant to help explain what is really going on, which I think fairly sums up the attitude towards the role of advanced stats in general. There’s a sort of scientific spirit of “things may look one way, but we can use unbiased measurements to see what’s actually happening.” In principle, this is a fine attitude, as we know about all sorts of biases that undermine our ability to judge.
What do we actually learn from these stats, though? The points about Minnesota and Boston I knew already; they were already pretty apparent. Saying that Colorado is subject to some bad luck right now, and that that explains their record, seems more promising, except that could also be explained by (as you point out) just looking at their shooting percentage. Ottawa, Columbus and Vancouver are all obviously going through goalie trouble.
My worry is that the Fenwick numbers you posted are meant to explain what we see and tell us what’s actually going on, but those numbers need in turn to be justified by the things we already know. Effectively, then, we’re doing the opposite; we’re using more basic stats and things we know about the teams to explain the Fenwick numbers.
This isn’t a damning indictment of Fenwick, nor of advanced stats in general, but I think it does point to a problem in how we treat these numbers, or what we expect them to do. I think this actually has a lot to do with the fact that these stats use shots as a proxy for the thing we really care about, which is possession. I don’t think most Sabermetric stats face the same problem, largely because what those guys realized was that what we actually care about is avoiding outs, or getting on base, not batting average or RBIs or whatever. We don’t have that luxury in hockey.
I’d be interested to hear what you have to say about all this (or anyone), as I’m not totally convinced that Fenwick and CORSI are barking up the wrong tree. Either way I think this stuff is interesting, at the very least.
Come get your duds in order...
If you can establish that one simple number like Fenwick is a very good way of summarizing a lot of complicated data that you CAN also know by scrutinizing a long list of details about the team, then it is a very efficient form of communication. In some sense this is what science is all about – finding simpler descriptions of complex things – cleaving nature at its joints, to use the old saw.
Maybe we can look at Chicago in depth and Fenwick only tells us what we expect to know. But then we can look at PHoenix or Ottawa or the Leafs and have a very quick summary insight into what’s happening with them.
And it CAN be insightful. A lot of us right now are assuming that the Leafs are playing somewhat over their heads. This data says that they actually are somewhat legit… that maybe their offence is unsustainably hot, but the reverse is true of their goaltending. That’s maybe something you could have figured out anyway, but it’s a nice efficient fast way to get there, and the quick description does suggest to you that if you’re crying “this will all collapse” that maybe you need to pause and look at this again more closely.
I get the efficiency argument, and if that’s all we’re after, and Fenwick does seem to match what we already take to be true, then that’s great. I just got the impression that these kinds of advanced stats were trying to tell us what’s actually going on, rather than just acting as a summary of what we know.
Come get your duds in order...
Science, as you say, is all about novel insights, but science can’t make those advances until it has suitably good measurement. Every time there’s been a big advance in how things can be measured (telescopes, electron microscopes, particle collides, inferential statistics, etc) you’ve tended to see bursts of increase in insights generated.
Advanced hockey stats are in their infancy. We’re at the stage of trying to figure out what the efficient and useful measures are right now. Perhaps later they will be used in novel was to generate better insights.
Overall I’d tend to agree, but I think there’s a significant difference between adv. stats like Corsi and Fenwick and the kinds of advancements you talk about (telescopes, microscopes etc…). Those advancements were all improvements on our ability to measure things. Corsi and Fenwick are simply shifts in what we think we should be measuring. I’m not against coming up with new metrics, but the work to be done is to show that the results are meaningful. We’re measuring a new thing; whether we’re also measuring the same thing in a better way is what needs to be shown. The new stat is supposed to explain what we see, but also itself needs to be explained by what we see, and that seems like it might be a problem.
Just trying to clarify my position. I don’t necessarily disagree with what you’ve said.
Come get your duds in order...
I think you are on the right track here. So far, Corsi and Fenwick with PDO only really help us with two things on a team level:
1. Checking whose results (wins, goals for and against) are likely to be sustained over the long term and whose performance is likely to be different in the future. This is particularly so because the possession metrics tend to be more stable when recorded at a better than average rate than save percentage and shooting percentage which tend to return to league or individual career averages over greater sample sizes.
2. Sorting our false narratives. This is maybe a subset of 1. but when Gabe Desjardins pops the Colorado and Minnesota balloons it is still fun to watch.
This development is not really the advancement in measuring anything, we always had the ability to observe shots that were attempted, hit the net or blocked, but an advancement in the rigorous recording of these events and then being able to process the data in useful ways.
What these numbers do not yet tell us is what it is that teams are doing that lead to increases in these numbers. I think we can all agree that the most effective way to increase possession is not to take a crap load of low percentage shots. What is really leading to the increased percentage are things like a higher proportion of successful zone entries and exits, loose pucks recovered, puck battles won, successful pass attempts. Many of these things could be observed, but they are not yet. We are starting to see an early wave of this kind of data being done by interested people in the public eye, but my suspicion is teams are already tracking this data.
Gabe has also suggested that RFI tracking of every player and the puck would render a wealth of interesting data. I agree. That would be the kind of advance in measurement that you are talking about.
Nice description
the other thing to remember is that all measures have built in assumptions. Bench press measures strength, but it assumes that a person with strong pecs would also have strong legs and biceps and what have you, and that their arms are fully operational, and that they aren’t additionally encumbered by weights, or tired, or short of breath, or sick… Those things don’t show up in your bench press number, but most of the time they’re reasonable assumptions, making your bench press stat useful, even if it isn’t bullet proof.
As you say, a team could uselessly inflate their corsi numbers by just firing pucks at the net from wherever the hell they were on the ice, as soon as they get anywhere over the blue line. They’d get a lot more shots, and not many more goals.
But under the circumstances of a normal well played game of hockey, fenwick seems to correlate enormously highly with offensive zone time, etc (see whoever it is who’s doing that counting most recently – they’re finding the numbers track very closely). And Fenwick is much easier to get than having to manually code time of possession in zones, so if it gets you the same info with less work under normal game circumstances, that makes it really useful, and you can use it to start building interesting models that start really testing more complex hypotheses. Yes it’s a proxy, not a direct measure, but we do that ALL THE TIME in science. Molecular chemists can’t SEE atoms interacting they can just infer what’s going on based on the aggregate behavior of millions of them being visible.
It may be that as we get more sophisticated about this stuff we start noticing times and places where corsi gives you an importantly different answer than, say, O zone possession time, and perhaps when we do that will teach us something important about the game.
One step at a time :)
I totally accept the correlations of corsi/fenwick to possession to winning, especially over the long term, especially at the team level.
Where I would like to be able to get to understanding is why the relationship breaks down. Why does a team with good possession metrics sometimes not post the expected results over what might otherwise be considered a sufficiently large sample size for this relationship to come into focus. I suspect a large number of those cases will be goaltending (see this season Harding, Josh and Mason, Steve).
There are cases where even when we see reasonable goaltending, the team still is not posting results commensurate with the possession rates. Take, for example, the Colorado Avalanche in 2009-10. Their shooting percentage was high, but if that is lucky, how did they manage to sustain such luck for so long? I know Gabe has the prize out there for proving shot quality as a repeatable skill, I just don’t know how we can chase that down based on the information and resources currently at our disposal.
I recall a blog (I think copper oil) that described a teams chance at winning as:
33% random luck + 33% skill (measured by corsi) + 33% other (PK, PP, coaching strategy (trap), exceptional talent like Thomas in net or Kessel’s shooting percentage, etc). Percentage allocation maybe off but close enough.
At risk of stating the obvious, on any given night a less skilled team can beat another team based on luck and another variable. And his bigger point was to not focus on statistics (which I tend to do because it can be measured and described) and lose sight of luck that maybe just as significant factor on any given night as skill.
Past luck does not determine future luck.
by stevesmith19 on Nov 24, 2011 3:54 PM EST up reply actions
They call that the gambler’s fallacy.
The Leafs are my Rushmore
Certified Grabbo Lover and member of the PPPPP
I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 7:06 PM EST up reply actions
It is true that for a given probability, results will tend toward a particular result over a long enough time span. That is to say that, while past luck does not directly affect future luck, with a large enough sample you’re very likely to see similar trends in both directions at various times.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 7:15 PM EST up reply actions
Corsi and Fenwick have both been shown to be a better predictor of future wins on the team level than “standard” boxcar stats have.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 12:43 PM EST up reply actions
Can anyone link me to the evidence for this assertion? I’ve heard it a number of times, I believe it, but it occurs to me that I haven’t actually seen the source.
By the way, great post Steve. Clear explanation and Fenwick percentage seems like a very useful expression of the stat.
Oh, I'm sorry, just one moment. Is this a five minute argument or the full half hour?
Also, won’t road Fenwick % still take into account inflated home shot numbers? If it’s a percentage of total Fenwick events, then we’re still including home shots in the calculation. If the bias for the home team isn’t the same across the league, won’t that skew the results a bit?
Come get your duds in order...
That isn't the point
The point of using road numbers is to minimize the impact of individual biased scorers. You’re spreading things out amongst road scorers for every team rather than relying on the same scorer at home for the data. It reduces bias, doesn’t remove it.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 11:48 AM EST via mobile up reply actions
Do you really love the lamp, or are you just saying that because you saw it?
The Leafs are my Rushmore
Certified Grabbo Lover and member of the PPPPP
I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 11:20 AM EST up reply actions 5 recs
Happy American Thanksgiving .. to any USA Maple Leaf Fans
and to all the Canadian Maple Leaf Fans.. .. Happy Thursday !!
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
Gotta love Thursdays
99% of player salaries are payed out to only 1% of players. #OccupyNHL
I'm a Twitter twat.
Tomorrow is Friday, and Saturday comes afterwards.
99% of player salaries are payed out to only 1% of players. #OccupyNHL
I'm a Twitter twat.
Only if there’s a random rapper for no reason back there, ‘cause you know, it’s not a real song unless there’s a random rapper.
-"I'm not drinking and driving, I'm driving while I'm drinking....Right boys!?"
Lest we forget: Brett Lebda
This is the major problem with my life. Not enough random rappers. I sometimes wonder if it’s even a real life.
Well, we can be reasonably certain it’s not a thuglife.
This space for rant...
by fair_n_hite_451 on Nov 24, 2011 1:27 PM EST up reply actions
That’s what Tuesday said. BCWW.
I've been looking at the sky
by Back In Black on Nov 24, 2011 1:51 PM EST up reply actions
I think it should be noted that road-tied corsi numbers are pretty small sample at this juncture so they could be somewhat misleading.
I was TOTALLY just going to post the same thing.
The Leafs are my Rushmore
Certified Grabbo Lover and member of the PPPPP
I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 11:22 AM EST up reply actions
and that is totally
Valid but I’m mainly making an effort to introduce the stat to people so they know wtf we’re talking about down the line.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 11:45 AM EST via mobile up reply actions
And you've succeeded
Because I never had any idea wtf Corsi and Fenwick were until now, so thanks for the post. Very informative.
99% of player salaries are payed out to only 1% of players. #OccupyNHL
I'm a Twitter twat.
PS follow this guy on twitter @Kent_Wilson
"You have to learn the rules of the game. And then you have to play better than anyone else."
Albert Einstein
by Say *plan the parade one more time*... on Nov 24, 2011 6:08 PM EST up reply actions
n sports like football (all versions of it – Canadian, American, European, Rugby, etc.) the key stat for most astute observers would be possession.
Actually in American football it turns out that possession isn’t generally as important as explosiveness. Having a lot of possession is great if you can get up early and then keep the ball away from the other guys, but it also means you have to keep running a lot of plays for low yardage, which is a lot of opportunities to have a few things to wrong and then have to punt. All else equal being able to break off big plays (one pass for 40 yards or a long touchdown) tends to be more predictive of success. Just FYI.
See here for a fascinating read on the “four truths” of football metrics, from one of the smartest analysts out there. This is Truth No. 2: “Big plays win games.”
As a proponent of that fact that players can drive shooting percentage and shooting percentage matters a lot in scoring goals, I think the same idea is true of hockey too. When you are trailing, you need the Crosby’s or Ovechkin’s to score you a goal and get you back in the game and a big reason why they are so good offensively is they can drive their teams shooting percentage up. This is like the “big play” in football.
Now, shooting percentage at the team level varies less than at the player level so it isn’t quite as important to factor into the equation but one thing I noticed in my research is we can better predict wins if we incorporate fenwick % when down a goal and fenwick % when leading into the equation. So, instead of taking fenwick % when game is tied, take (fenwick% tied + fenwick% up1 + fenwick% down1)/3. When the game is tied both teams are typically playing a neutral style of game, when leading they play a defensive style game, and when trailing they play an offensive style of game. The good teams are the ones that can do all three well, and if they team can also put up a good team PDO they will be a great team.
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by HockeyAnalysis on Nov 24, 2011 12:09 PM EST up reply actions
Interesting. Out of curiosity, how well do the two formulas correlate with each other and with win percentage?
by stevesmith19 on Nov 24, 2011 12:15 PM EST up reply actions
It’s been a year or two since I looked at it so I don’t recall the exact numbers and I am a bit busy to go dig it back up, but if I recall correlation improvement using my formula while not insignificant, wasn’t earth shattering either, but certainly worth using. Maybe I’ll dig it up some time.
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by HockeyAnalysis on Nov 24, 2011 12:40 PM EST up reply actions
i just ran some numbers:
Road Fenwick with point %: r = .245
PDO with point %: r = .744
Road Fenwick with PDO: -.13.
So basically, I’m not really sure that Fenwick is useful at all. It’s not only poorly correlated with win %, it’s negatively correlated with things that are correlated with points %.
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 12:50 PM EST up reply actions
at least, based on the numbers Steve’s given us…
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 12:51 PM EST up reply actions
yeah, this is why i’ve never been a fan of ‘possession’ stats. you can shoot all the shots you want and block 100 shots a game, but ultimately wins are determined by goals, not shots.
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 12:57 PM EST up reply actions
I guess its technically possible to have extremely strong Corsi, for example, and not score a single goal all year.
by Self Destructive Zones on Nov 24, 2011 12:58 PM EST up reply actions
right. which i guess some would argue would be ‘unlucky’. so the thing that measures ‘luck’ actually correlates well with winning.
which is to say, i guess, what others have said. that possession stats tell you whether a team is better than their numbers appear. except i’m not sure that a higher fenwick or corsi automatically means ‘better’ team.
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 1:08 PM EST up reply actions
I think Gabe stated that luck plays a major role in both shooting and save percentage, and that was the main reason why he prefers to use PDO if he wants to look at one stat only to evaluate teams.
"We are all agreed that your theory is crazy. The question that divides us is whether it is crazy enough to have a chance of being correct."
- Niels Bohr
Sorry, unauthorized hotlinking of copyrighted material not permitted.
Sample size is too small here. I’ll see if I can dig it up, but I’ve seen evidence that Fenwick is a very strong predictor of future success on the team level.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 1:07 PM EST up reply actions
This isn’t exactly what I was looking for, but here’s a pretty detailed post on the usefulness of Corsi and Fenwick:
http://objectivenhl.blogspot.com/2011/02/shots-fenwick-and-corsi.html
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 1:10 PM EST up reply actions
Using
4 seasons worth of data, and wins (including OT and SO) the r value is 0.53531
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 2:52 PM EST up reply actions
Oh
for Road Fenwick % While Tied.
So it’s not as significant as PDO – but that makes some sense as PDO is just the sum of SV% and Shooting percentage… obviously teams with higher PDO prevent more and score more goals respectively.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 2:54 PM EST up reply actions
Only if they generate equivalent shots. To score more goals you can either maintain your shooting percentage but increase your shots, or maintain your shots but increase your shooting percentage, or increase your shots and shooting percentage. Similarly, but opposite, for decreasing goals against.
What is the r value for PDO? If PDO has a higher r value, then what I have been saying at the player level is true at the team level too.
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by HockeyAnalysis on Nov 24, 2011 3:04 PM EST up reply actions
I don't have
the PDO numbers handy, so I don’t know, but I’d assume it’s higher than 0.535
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 3:09 PM EST up reply actions
but
I don’t think that proves anything w.r.t. your assertions about players ability to drive SV% or SH% on a team wide basis.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 3:12 PM EST up reply actions
if you could show
that teams have a consistent ability to produce an above average PDO season to season, then it would make sense. Otherwise it’s sort of difficult to argue one way or another.
The fact that PDO correlates to winning doesn’t mean that it is a sign of a better team.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 3:12 PM EST up reply actions
True, but I can show it on a player level so it isn’t a stretch to assume that teams have that ability too.
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by HockeyAnalysis on Nov 24, 2011 3:19 PM EST up reply actions
We'll have to look into it
but the level of turnover on a team year to year also impacts upon it so it’s sort of a grey area.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 3:24 PM EST up reply actions
Yeah, you might want to not include teams with a high turnover of core players in the analysis (i.e. Florida this season).
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by HockeyAnalysis on Nov 24, 2011 3:25 PM EST up reply actions
Sorry, you can show repeatability at the player level for on ice shooting percentage and on ice save percentage – or just personal shooting percentage and save percentage. I have seen latter, I don’t think I have ever seen the former. If you have an article I would read it.
I don’t have an article specifically dealing with on-ice shooting percentage but I can post the numbers here. The following are year vs year on-ice fenwick shooting percentage correlations of all forwards with >500 minutes of 5v5 ice time in each of the past 4 seasons.
2007-08 vs 2008-09 R^2 = 0.0620
2008-09 vs 2009-10 R^2 = 0.0716
2009-10 vs 2010-11 R^2 = 0.0793
Yes, I know what you are thinking. Those are pretty weak correlations. Yes, they are. But now let’s look at 2 year vs 2 year.
2007-09 vs 2009-11 R^2 = 0.241
That gives you r=0.49. So, in one year of data there is significant randomness which is why the correlations of 1 year vs 1 year are so poor. There are 170 players used in my study and many of them are 10-15 goal guys, some less than that. That’s is not a very large sample size to draw conclusions from. But increase the sample size and we really start to see a players ability to drive his on-ice shooting percentage.
This is why I am such a proponent of using multiple seasons of data when evaluating players.
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by HockeyAnalysis on Nov 24, 2011 4:00 PM EST up reply actions
Very cool. Do you happen to have a similar 2 year correlation for S/60?
by stevesmith19 on Nov 24, 2011 4:02 PM EST up reply actions
Correlations for fenwick for per 20 minutes.
2007-08 vs 2008-09 R^2 = 0.3706
2008-09 vs 2009-10 R^2 = 0.3613
2009-10 vs 2010-11 R^2 = 0.3558
2007-09 vs 2009-11 R^2 = 0.4348
Certainly better than for shooting percentage but interesting to note that there isn’t near as a significant gain going to 2 years vs 2 years.
My presumption is that at 3 and 4 years fenwick shooting percentage gets even closer to representing the players true ability but I don’t have 6 years of data to do a 3 year vs 3 year correlation and at that point career progression could start having a significant impact.
In this article I look at how well FF20, FSH% and GF20 (goals for per 20 min.) are at predicting future goal scoring rates. At 2 years of data GF20 significantly better than FF20 or FSH%.
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by HockeyAnalysis on Nov 24, 2011 4:12 PM EST up reply actions
Dynamite stuff. Really earning your screen name there :)
One of the reasons it might take longer to see shooting percents become consistent than fenwick is there may just be less variability in the data. If all the players have very similar shooting percentages over a whole year, then you would have to average a LOT of numbers together before you would start to be able to tease apart such differences as do exist.
The difficulty is solely due to small sample sizes. There is actually significantly more variability in 4-year SH% than there is in FF20. See this article for details.
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by HockeyAnalysis on Nov 24, 2011 5:48 PM EST up reply actions
I’m impressed with your stuff. I’m not a hockey stats guy but i’m a social scientist so I do appreciate good stats and analysis in general.
(and I stupidly clicked your link rather than control clicking it, so now my browser has lost track of which comments I’ve already read and which I haven’t. Grrr!)
To follow up, though, you would EXPECT goals for to be the best predictor of future GF, as it’s a closer match. The others are just components that lead towards goals, so on their own you would expect them to predict only part of a player’s consistency in goal scoring.
That said, tracking shots created and shooting percentages could certainly be valuable here if you had reasons to believe that a specific part of a player’s game had changed – perhaps if they move teams, for instance, you might expect teammates to have a stronger effect on your fenwick than on your shooting percent. I don’t know, I’m just making that up, but it’s the kind of empirical question you can start checking in to once you’ve figured out the basics of what you want to measure, and the technical details of how to score it (fenwick vs. corsi, percents vs. raw numbers vs. per 60’s, etc)
To follow up, though, you would EXPECT goals for to be the best predictor of future GF, as it’s a closer match.
Sure, but there seems to be an extreme adversity to using goals as an evaluator of talent as strange as that sounds.
That said, tracking shots created and shooting percentages could certainly be valuable here if you had reasons to believe that a specific part of a player’s game had changed – perhaps if they move teams, for instance, you might expect teammates to have a stronger effect on your fenwick than on your shooting percent.
Sure, style of play is definitely a factor in these stats. Detroit definitely plays the puck control game but their shooting percentages are not near as high as some other teams. Other teams play a more high risk-high reward game. I am not saying we shouldn’t look at the component skills of scoring/preventing goals, but that we should not be using corsi/fenwick as an indicator of overall value.
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by HockeyAnalysis on Nov 24, 2011 5:54 PM EST up reply actions
The problem with using goals as an indicator is just sample sizes. Unless you look across a lot of seasons, and are dealing with very talented players the numbers are too small I would think. It’s not like basketball where players are scoring 4-60 points every game, giving you endless detail to break down.
But on a more philosophical front it seems to me that your problem isn’t with corsi per se, it’s with using ONLY corsi without the context of finishing ability. But the rub is that we don’t really have a good measure of individual finishing ability (without several seasons of data on someone), because goals are too rare. Shots aren’t, goals are. If you score on 10% of your shots, you need a sample size almost 10 times as big before you’re getting the same level of confidence to know when goals happen.
So people describe players using the only half of the data they have freely available, and it paints a picture that is good but incomplete in important ways.
That a good summary?
Sort of. My problem with corsi is not so much with corsi itself but with how some corsi advocates give it too much value in player evaluation while also frequently dismissing shooting percentage as a talent.
My goal is to find the best way to fairly evaluate players. Using corsi and corsi/fenwick derived stats is not the best way to do so. Even with just a single season of data, GF20 is an equally good predictor of future GF20 as FF20 but beyond 1 year of data GF20 is by far the better predictor. So, why not use GF20 as our base evaluator of offensive talent for every player that we have at least one full season of data for? For most players we have multiple seasons of data so why not use it and get a better evaluation of the player.
For those players with less than one full season of data for, fine, use corsi/fenwick but put a disclaimer at the bottom saying something to the effect that even though the player has a good (or bad) corsi/fenwick rating it does not mean he is a good (or bad) player because corsi/fenwick only tells us something about puck control but puck control is only about 40-45% of being a good player.
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by HockeyAnalysis on Nov 24, 2011 6:50 PM EST up reply actions
Honestly I’m not well enough versed in the issues to give a strong reading on that beyond “it sounds reasonable”, but I think a part of the problem you’re going to run into pushing that is that it’s too simple to appeal to proper stat nerds. If it’s something that even Healey could think up, then it’s like you can’t possibly be trying hard enough. I mean, sometimes the screamingly obvious solution is the best one, but that doesn’t mean everyone is going to like it :)
Can you give an example of someone who dismisses SH% as a talent? Shot quality is not the same as SH%; it’s self-evidently true that some players consistently shoot at a higher , the question is why. Some people believe that shot quality is a minor factor, while other things like shot location are much more important, but I’m unaware of anyone who thinks there’s no element of talent in SH.
It’s certainly true that over a large enough sample, there are very few players in the NHL who can shoot higher than, say, 15%, and it’s also true that the players who score the most goals tend to be the players with the highest shot totals rather than the highest SH%.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 7:09 PM EST up reply actions
Why not say that for each player you need to know the shots they drive AND their shooting percent? Sort of like to describe a normal distribution you need a mean AND a standard deviation
Why not say that for each player you need to know the shots they drive AND their shooting percent? Sort of like to describe a normal distribution you need a mean AND a standard deviation
I could accept that but how often does that occur? Do people properly explain that shooting percentage is at least, and probably more, important to scoring goals? Or, why not just use goals as the basis for the analysis unless there is a specific reason you want to look at the component parts?
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by HockeyAnalysis on Nov 24, 2011 8:18 PM EST up reply actions
Can you give an example of someone who dismisses SH% as a talent?
Gabe Desjardin’s. He believes that players can’t drive (or suppress) shooting percentage. He had a challenge out for people to prove or disprove that because he thinks it doesn’t exist. I have had several debates where he seems to insist that shooting percentage is luck driven and not a talent.
Another one is the author of The Puck Stops Here blog. Go read some of the discussion we have had on his and/or my blog. He doesn’t believe shooting percentage is a repeatable talent.
it’s also true that the players who score the most goals tend to be the players with the highest shot totals rather than the highest SH%.
Highest shot totals yes, but not highest shot rate (i.e. shots per 20 minutes). Shooting percentage correlates much better with goal scoring rates than fenwick rates do. It really isn’t close.
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by HockeyAnalysis on Nov 24, 2011 8:16 PM EST up reply actions
Yes. Shot totals and goal totals are highly correlated, but only because shot totals and goal totals are highly correlated with TOI. Factor out TOI and shooting percentage becomes the more important factor in scoring goals.
I haven’t posted anything on this yet (and may not) but I was looking at FF20 vs TOI and SH% vs TOI and it is clear that coaches generally dole out ice time according to a players SH%, and not according to a players FF20. Preliminary results show that SH% seems to correlate with TOI much better than FF20 which indicates to me that coaches believe that is the more important skill.
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by HockeyAnalysis on Nov 24, 2011 8:29 PM EST up reply actions
I think you’ve completely misunderstood Gabe’s shot quality challenge. The challenge, as I understand it, is to prove that there are players who score more because they have a better shot, for example, by showing that there are players who consistently outshoot the expected shooting percentage based on shot distances. I can’t speak for Gabe, but I think you’re misrepresenting the arguments he’s made.
Shooting percentage correlates much better with goal scoring rates than fenwick rates do. It really isn’t close.
This is a straw man; I don’t know of anyone who believes that Fenwick is a good predictor of individual goal-scoring talent. Proponents of Fenwick argue that it is a good proxy for puck possession, and that players who have good puck possession numbers will tend to be successful because their team has the puck more frequently than the other team, increasing your team’s chances to score and decreasing the other team’s. No one, to the best of my knowledge, thinks Fenwick is a predictor of individual goal-scoring ability.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 9:11 PM EST up reply actions
Fenwick is a predictor of individual goal-scoring ability.
I wasn’t referring to individual goal scoring, I was referring to team scoring while the individual was on the ice.
increasing your team’s chances to score and decreasing the other team’s.
I am not disputing that improving your corsi/fenwick achieves the above, just that increasing your shooting percentages has greater impact on your teams scoring.
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by HockeyAnalysis on Nov 24, 2011 10:28 PM EST up reply actions
What is a better predictor of future success for a team – its current SH% or its current Fenwick ratio? Which tends to be subject to more regression (thus indicating it’s subject to a greater degree of luck)?
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 11:07 PM EST up reply actions
Here’s a related thought experiment:
At the 27 game mark (roughly 1/3 of the season), you’re forced to make a bet on which of two teams will win more games in the remaining 2/3 of the season. Which of these two teams do you place your money on:
1. The team with the best team SH% through 27 games.
2. The team with the best Fenwick ratio through 27 games.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 11:18 PM EST up reply actions
And for the purpose of this thought experiment, those are the only two pieces of information you have available to you.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 11:19 PM EST up reply actions
As for Gabe’s shot quality challenge, one question he posed was: Are there players or teams with the ability to drive or suppress on-ice shooting percentage? I have also had a few discussions with him where he openly questions whether a player has the ability to drive on-ice shooting percentage. See the discussion in the comments here as an example. I am pretty sure he doesn’t believe players can drive/suppress shooting percentage in any significant way, though it seems I may have opened his eyes a bit considering the fact he now has “shot quality” data on his stats site.
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by HockeyAnalysis on Nov 24, 2011 10:40 PM EST up reply actions
Gabe's shot quality
is just a comparison of expected and actual shooting results based on shot location.
I think the issue is the sustainability and repeatability of the values year over year.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 11:13 PM EST up reply actions
Yes, there are sample size issues. I admit that. Where Gabe goes wrong is when he concludes that because sustainability is difficult to identify it doesn’t exist as a talent. Instead I increased sample size and showed sustainability 2yrs vs 2yrs.
So, the question is, do we stick with one year of data and the inferior corsi/fenwick as an evaluator of talent, or do we increase our sample size to 2 or more years and get a better evaluation of player value by using goals as the metric of choice. Considering we have 2+ years of data for the majority of players in the NHL and that it provides a far better evaluation of the player (and predictability of future performance), the answer seems pretty clear to me. Multi-year goal based analysis.
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by HockeyAnalysis on Nov 24, 2011 11:34 PM EST up reply actions
Goal analysis?
But it isn’t a goal-scoring competition
My rambling tweets
Winning is a habit. Unfortunately, so is losing - Vince Lombardi
Exactly. Just like the Oscars, this is a shot directing competition. The smart money this year is on scores, says he.
by Spezzal Teams Playa on Nov 25, 2011 2:21 AM EST up reply actions
I assume that's road fenwick WHEN TIED
because otherwise you’d expect a negative correlation. If you’re better at putting the puck in the net and keeping it out your net then you will tend to be up a goal or two, and the resulting score effect will tend to reduce your Fenwick.
yes, it’s tied.
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 1:36 PM EST up reply actions
i’m using the table Burtch provided.
Move along. Nothing to see here...
by Van Ryn's Neurologist on Nov 24, 2011 1:36 PM EST up reply actions
hm.
then mostly I’m thinking we’re in 3SA territory. Talk to me about which stats are useless when it comes from a big enough data set to get stable results and reliable estimates… and then we can start looking at indirect effects, suppressors, etc, and the fun really starts :)
I posted
the 4 year correlation above. It’s significant.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 2:54 PM EST up reply actions
The
numbers for Fenwick% when close are available on Gabe’s website if you prefer to use those.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 12:17 PM EST up reply actions
The problem with close is it more mimics game tied. I think the benefit was treating tied, up and down as equal parts, not lumped together which biases towards tied because game tied situations occur far more often. We really want to measure a teams ability to protect a lead or ability to come back from a deficit.
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by HockeyAnalysis on Nov 24, 2011 12:43 PM EST up reply actions
he also
has the up1, up2, down1, and down2 data available. Go the site and look if you’re curious.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 2:55 PM EST up reply actions
Yes, I have all that data handy too (well, mostly, it isn’t as organized at the team level as I would like at the moment), just haven’t looked at it at the team level for a while.
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by HockeyAnalysis on Nov 24, 2011 3:05 PM EST up reply actions
Just wondering, what’s a significant deviation from PDO that would tell you the team is lucky or unlucky? Like, a minimum deviation value or something?
"I like this one for everything & that one for the chicken" - GeniusInFrench
Toronto: The city that will gladly take your garbage and turn it into gold
On the player level, players typically settle into the 970-1030 range with only a few exceptions outside that range. Haven’t worked with team data much but I suspect the range would be a fair bit smaller at the team level.
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by HockeyAnalysis on Nov 24, 2011 12:12 PM EST up reply actions
Thank you.
I read PPP a lottt, but don’t post that often; I enjoy the banter/discussion and have learned a lot over the last little while.
The stat discussions I always skip though, because I never really understood them fully, but this helps a LOT.
Thanks!
"His body is composed entirely of wood; essentially he is a living breathing maple tree." -The Maple Leaf, Guardian Project
ah, a stats post

Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 12:04 PM EST reply actions 9 recs
how about this Gif ? Isnt this funny ?
Is this the way Wade Belak got around on the ice ?

FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
what the hell?
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 7:52 PM EST up reply actions
.......

The Leafs are my Rushmore
Certified Grabbo Lover and member of the PPPPP
I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 8:00 PM EST up reply actions 2 recs
wait… Deja Vu here…
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
yup, you’ve definitely told unfunny inapropriate jokes before
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 8:27 PM EST up reply actions
Resident Internet Tough Guy
Even on a Thanksgiving Holiday when people are supposed to be kind and thankful and giving towards others…..the Resident Internet Tough Guy still reigns .. shall we say… a massive Phallus.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
right, you show up and make a joke about a much beloved hockey player that recently passed away and I’m the dick.
I understand you have had some tragic happenings in your life recently Rob and I feel awful bad for you about that, but don’t for one second think that buys you a free pass to be an ignorant ass around here. Stop while you are ahead
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 8:38 PM EST up reply actions
Actually.. I didnt mean Wade Belak… I meant Lebda… So … I do apologize for using the wrong name.
Actually.. I didnt mean Wade Belak… I meant Lebda… So … I do apologize for using the wrong name.I would never put down Belak. He actually was a good player.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
also if this gets bad, remember that YOU started with the insults so don’t you go crying for pity and play that fucking victim game you always do, I am in no mood to pull punches today
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 8:43 PM EST up reply actions
It's bad timing Bob
When Belak was playing for the leafs most people here would have found the joke pretty funny. But recent circumstances but this into a different light.
I do apologize.. I meant Lebda. funny joke .. but wrong name.
ouch.. ooopss.. oh man … wow did I gaffe that one.
ouch.. ooopss.. oh man … wow did I gaffe that one.I once meant to say Leclair and I said Renberg. I once meant to say Potvin and I said raycroft … it wasnt meant to be Belak in the making fun how a player skates.. it was meant to be Lebda.
ouch.. ooopss.. oh man … wow did I gaffe that one.I once meant to say Leclair and I said Renberg. I once meant to say Potvin and I said raycroft … it wasnt meant to be Belak in the making fun how a player skates.. it was meant to be Lebda.oh man did I botch that up.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
no. its not all good. Wow Do I really apologize. Never meant to make fun of Belak because that was a total shame and a mega tragedy. He was a dang good gritty player. I totally screwed up on that gaffe.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
Well, I don’t celebrate Thanksgiving for obvious reasons so I can say ‘go away, you are a complete idiot and I’m not surprised you got booted off the Flyers’ site’ without giving half a shit about it being a magical day where one is not allowed to call somebody else on being a knob.
by Be26 on Nov 25, 2011 6:41 AM EST up reply actions 1 recs
your entitled to your opinion.
May you have a wonderful day.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
Normally that’s me too, but I did enjoy reading this one.
Not enough to hunt down these numbers in the future on my own … but I did glaze over and fall asleep at my desk either.
So, progress!
This space for rant...
by fair_n_hite_451 on Nov 24, 2011 12:27 PM EST up reply actions
Great post Steve, Thanks.
Twitter may not appreciate you, but I sure do!
by Self Destructive Zones on Nov 24, 2011 12:42 PM EST reply actions
Advanced stats
To me I always compare it to baseball, where to me it makes sense to get a better idea of the individual contributions of players. In hockey, while I see their application on a team comparison level, I remain ignorant as to how advanced stats give an accurate portrayal of players on an individual basis independent of team performance.
My rambling tweets
Winning is a habit. Unfortunately, so is losing - Vince Lombardi
It’s harder to be sure. But just because something is hard doesn’t mean we should just fold our tent and give up now does it.
This is, BTW, often a reaction I see from physical scientists when looking at the social sciences. They are often very very smart people, yet they can be incapable of understanding how social sciences work. They are used to being able to control every aspect of the environment of the things they study, and so as soon as they hit a few road blocks on being able to do that they throw up their hands and declare that the whole thing is impossible. It’s a bit sad really.
But it can be taken too far. I just saw a social geographer talk about preparing a model for something like water usage by people and its effect on the hydrological cycle, and one of their parameters was “Sustainability”. I was very interested in what value of Sustainability they were going to plug into Matlab. 7.4?
The point is that success in hockey, both at the team and individual levels (like “Sustainability”) is a combination of so many factors (luck, shooting%, shot quality, number of back-to-back games, quality of officiating, quality of stadium catering, you can add your own 50 factors) that taking numbers so inherently simplistic like Corsi or Fenwick seems almost pointless. The fact that they have to be so highly modified (just when tied, just on the road) means that you’re taking a not-huge sample size and trimming it down to bare bones, possibly to the point of irrelevance.
I think applying stats like these to the hundreds of factors that go into a team’s/player’s success puts you in the same boat as the “Sustainability” researcher: it’s not an inherently intractable problem, but to really do it justice requires so many inputs and so much computing power that it’s not unreasonable to throw up your hands and declare it impossible.
by DrExcitement on Nov 25, 2011 11:31 AM EST up reply actions
I’m really glad your guy had sustainability in there. Just because something is hard to think about does not mean it isn’t important. And if you leave important stuff out of your model then you can end up in spectacularly dumb places.
Here’s an example:
You are building a shipping service and need to figure out how to reward drivers. It’s very easy to accurately measure delivery times, but it’s very difficult to measure “driving carefully”. So you just set up your rewards only for delivery time, and nothing for careful driving. The result is going to be an awful lot of accidents, stressed out drivers aking mistakes, hurting people, losing cargoes, and, if nothing else, driving up your insurance costs. Careful driving may consist of so many things that are difficult to measure (proper eye movements to check blind spots, situational awareness of other cars on the road, paying attention to signs and laws and speed limit changes, etc… but that doesn’t mean you should build systems that ignore it.
You can build a big huge aquifer system but if you don’t build it sustainably you can build one that eventually starts sucking in salt water from nearby seas, for example, at which point all of your work is ruined because the aquifer becomes permanently unusable. And if you came back to the guy who built that aquifer afterwards and screamed at him for incompetence you wouldn’t be that impressed if he said “there was no single objective number I could put into my equation for sustainability so I left it out”. That’s not a guy who gets promoted there, that’s a guy who gets fired and doesn’t work again.
I’m not saying that certain concepts should be ignored because they’re too all-encompassing to be easily handled, I’m just saying that if you’re going to talk about things like “Sustainability” or “Success in Hockey”, you can’t just limit yourself to “Amount of pollutants in groundwater” or “unblocked shots taken in road games with the score tied”.
There are way more factors inherent in these sorts of concepts that aren’t being taken into account, and in order to really tackle a problem in a way that means anything, you have to worry about ALL of them, or at least a large representative subset of them. And to do that, you need to input a huge range of variables and devote a huge amount of computing time. My geographer pal was embarking on a multi-year, million-dollar project, and that’s just to handle that kind of data from a handful of locations in his model.
I guess I’m saying that I’d be willing to sacrifice quantitativeness for a more holistic view that more accurately represented the complete spectrum of factors that go into hockey success. And I’m a physical scientist.
by DrExcitement on Nov 25, 2011 11:54 AM EST up reply actions
I think there’s different approaches to understanding. One is to try to come up with a model that is as all-encompasing as possible, that tries to model as many aspects as possible in order to come up with a complete and fine-grained understanding. That’s a completely legit approach.
There’s another, though, which tries to cleave nature at its joints, and to say “yeah, this all looks unbearably complicated and confusing, but if you look at these simple few things, then you can very quickly get to the essence of what’s going on.” It’s what we have to do in psychology and markets all the time. You can’t possibly model every single psychological input and process going on in someone’s head, but you can start to get a pretty good prediction of their behavior towards a product if you just know, say, their overall attitude towards it, and some basic features of the situation they’re in. You don’t even TRY to model every detail, you just search for a few key levers which tell you the most about what is going on.
Some people prefer the one approach, some prefer the other, but neither is inherently better, they just have different strengths and weaknesses – they trade off accuracy for parsimony differently.
Understood.
So the question becomes: What inputs do we use? I’m not positive what the answer to that is, but I’m pretty darn sure that it’s more than “unblocked shots in tied games on the road”. That’s not cleaving Nature at the joints, that’s trying to represent Nature by its pinky toenail. I’m sure you can get a surprisingly large amount of information from a pinky toenail, but not nearly enough to make the kinds of sweeping generalizations that are being made based on the modified Fenwick number (to back out of that analogy with a modicum of dignity).
Anyway, I agree that one doesn’t have to know the position of every rubber molecule to know what a puck’s going to do when it leaves the stick, but I’d like to see a more robust understanding of what inputs are the most meaningful to hockey success before we worry too much about applying statistical rigour to the numbers.
by DrExcitement on Nov 25, 2011 12:17 PM EST up reply actions
The extent to which we are successfully predicting outcomes is an empirical question. Some element of performance is random, and some part is systematic. Fenwick gives us a read on some portion of that systematic component. We can tell how much by looking at the extent to which it predicts future wins – and that analysis tells us that it’s not a bad start. Maybe we can add observations of more variables that will let us get even more accurate, and that would be a good thing, and I don’t think anyone has stopped looking for what those might be.
That said, there’s a cap on how good your predictions will ever be, because games have an enormous random component to them. Even if you could have the perfect proverbial God’s eye view of a team, where you knew exactly, and with total insight and certainty how good they were, and how good the rest of the teams in the league were, you would still be making a lot of mistakes in predicting the outcome of specific games. The team that you know, with absolute certainty to be the best in the league would still miss the playoffs some years, and would regularly be eliminated from the playoffs before winning the cup. They’d have a better chance than everyone else, yes, but the spread in skill between NHL teams is so small compared to the number of games they play that the percent of explainable variance is far below 100%
So let’s not rest on our laurels with fenwick, but let’s not be overly down on it either.
Yeah, for sure. I mean, Ottawa beat us.
And because it’s empirical, let’s approach it iteratively. I’m sure there’s a permutation of factors out there that will lead us to the kind of predictive/analytical power that we’re looking for. MAYBE Fenwick factors in there. But what (other) parameters are meaningful? Let’s deal with that question before we really get arguing about the application of stats to any one parameter. Our problem at this point isn’t “how should we modify the Fenwick number so that it best represents reality?”, it’s “what the hell are we even looking at here?”, which is a much bigger problem.
by DrExcitement on Nov 25, 2011 12:49 PM EST up reply actions
we’re looking for numbers that predict wins. Fenwick is a pretty good one, but if you can find better ones more power to you. The hockeyanalysis guy above claims he has some numbers that do a bit better, though other hockey stats people seem to be disputing it. personally I haven’t followed the details so I have no dog in the fight, but it’s certainly intriguing.
Intuitively we see the complexities of the game being played, and it seems like there MUST be some better measures… but trying to figure out what those would be is the hard part.
Well, DUH. But if we’re not willing to go through all the possible inputs and measurements (even those not currently being measured), and put them together in all possible permutations, then we’re not going to get where we want to be. Period.
Is that really, insanely, probably impossibly hard? You bet.
So does Fenwick serve our purposes adequately in the meantime? I still say no.
Can I ask a question, then answer my own question? Undoubtedly.
by DrExcitement on Nov 25, 2011 1:07 PM EST up reply actions
I’m not sure why you think people AREN’T sorting through the permutations. You’re acting like someone came up with this one time, and everyone just went along because they couldn’t be bothered to do anything else.
And if you define “adequately” as “significantly better than chance + our other alternatives”, then I disagree, yes, it is adequate.
I’m not saying no one is/has, just that we’re not there yet.
by DrExcitement on Nov 25, 2011 9:41 PM EST up reply actions
Why are you saying
No to Fenwick? have you READ any of the supporting documentation out there on it? Have you actually examined it’s value beyond this current posting (in which I included a caveat around it being useful over the course of a SEASON… not one game).
I just find it absurd that you’re basically annoyed that I’m trying to account for noise in the sampling by refining it. Why is that a problem?
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 25, 2011 7:33 PM EST up reply actions
I didn’t say that.
My “problem” (which isn’t really a problem, and certainly isn’t a reflection on you personally) is that when you take something already of less-than-conclusive usefulness and shave it down to very, very specific cases, you’re losing a lot of information that may or may not contribute to its value in the first place. It might seem like “noise”, but maybe the fact that there is unacceptable (to you) noise in the Fenwick data means that Fenwick isn’t that great of a metric, instead of the idea that it’s got some hidden kernel in there somewhere that’s really great to use, if only we exclude THIS information and THAT information.
by DrExcitement on Nov 25, 2011 9:45 PM EST up reply actions
the "noise"
is appreciably due to relatively large swings in recorder bias. Unfortunately that value exists in all shot recording, so using “sh%” is sort of flawed for the exact same reason.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 1:41 AM EST up reply actions
Well, sure. I’m not advocating using sh% exclusively either.
by DrExcitement on Nov 26, 2011 3:04 AM EST up reply actions
How does scoring chance differ from Corsi, Fenwick or SOG? I hear the term used but not seen a clear definition. It seems to be equivalent to hits/turnovers/takeaways.
Also from what I read, it seems Corsi or Fenwick was developed and better suited for team to team comparison rather than player to player comparison. What justification exists to apply it to the player level?
Corsi et. al. is just a count of shots. If the scvoring dude says it was a shot at net, then it counts.
Scoring chances is individual people watching the game on their own, and trying to categorize some shots as being better chances than others. Typically if it’s from between the dots, a deflection, etc.
So I take it that scoring chances are subjective (like turnovers and takeaways) so why would it be more accepted then the turnovers/takeaways? I’m guessing we trust draglikepull judgement of scoring chances but not necessarily some random dude in NHL arena counting turnover for example.
It shouldn't be
“more” accepted. There’s error with ALL measurement. Nothing is error free so you need to take it with a grain of salt.
That being said, there are reasonably acceptable ranges of variation that make the information useful.
The other question is whether or not it’s applicable to anything… if you can show that it makes winning more likely then it’s useful.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 3:16 PM EST up reply actions
There’s a margin of error in recording every kind of stat, but we at least have a pretty good idea of what a “shot” is, and a scoring chance is basically just a shot from a particular area on the ice. I don’t think there’s any clear agreement on what constitutes a “turnover”.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 3:27 PM EST up reply actions
Yeah, is it a pie or a danish?
The Leafs are my Rushmore
Certified Grabbo Lover and member of the PPPPP
I also write things about stuff over at the Leafs Nation
by Plea From A Cat Named Felix on Nov 24, 2011 3:33 PM EST up reply actions
Certainly it falls into the broader category of “pastry,” right?
by Self Destructive Zones on Nov 24, 2011 3:42 PM EST up reply actions
My wishful thinking...
Quantifying a shot.
Cameras record game from above and the sides. Find shot origin, horizontal velocity, vertical velocity, goaltender position relative to puck at start of shot, number of players screening. Also (since this could be important), if the puck goes in.
Combine them all in some way to get a shot rating between 0 and 1.
As an example, this might be a 0 and this might be a 1. Normally, the outcomes of those shots would be reversed, but we are talking about the Leafs here.
by stevesmith19 on Nov 24, 2011 3:50 PM EST up reply actions
Goaltender position would be almost impossible to measure. What if they’re moving, is it the position at the time of release or puck arrival, or when the player is deciding to shoot in the split second before their brain has time to tell their muscles? And what if the goalie is not moving but they’re in butterfly vs. standing up? And what if they have their arms in a funny position leaving one set of holes bigger than the other? And would hte shot have been aimed somewehre else if the goalie wasn’t in that position?
Number of players screening is similarly awkward. If someone skates by is that a screen? If their arm is there? How can you tell how bulky the player is and if their movements are particularly distracting or not?
The point isn’t that it’s impossible to tell if shots are of higher or lower quality, but that it’s only possible to measure these things with a certain amount of precission, and if you try to measure it more precisely than that you can certainly come up with numbers but you’re mostly fooling yourself that they mean anything. Stick to the level of precission you can get, and then get a big enough sample size that you can just average away the ambiguity. That’s how it’s done.
Wishful thinking no doubt. And the goalie/screening stuff was admittedly a bit silly. But I would love to see a publicly available record of objectively determined measurements (location, velocity, whatever) related to shots.
by stevesmith19 on Nov 24, 2011 6:12 PM EST up reply actions
I believe they have location of shots somewhere, and sometimes it’s coded by type (slap, snap, wrist, etc). Recording velocity is a bit unicorny, and I’m not sure how much it would add.
PPP’s own Ninjagreg runs a database where you can look up shot locations by player or team over the past few seasons.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 7:12 PM EST up reply actions
I’ve been comparing Scoring Chances to other data like Corsi in my Puck Possession series of articles here.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 2:31 PM EST up reply actions
Personally, I think I can deal with some inconsistency in terms of Fenwick scoring.
Since we’re talking about 20 games, I’d rather have a larger sample size, so I tend to look at the Leafs’ Total Tied Fenwick.
The picture doesn’t look so rosy, there.
Not followin' @JPNikota on Twitter? Oh, you better believe that's a paddlin'.
but to use it for comparison
the biases kind of throw you for a loop. Saying you’d prefer to have a larger sample is great, but not if that sample is measured by completely different people and you don’t account for the error.
I admit the issues around sample size are pretty large, but I don’t think it’s completely wasted as information goes either.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 2:59 PM EST up reply actions
If we were really sophisticated we could come up with some kind of model that would estimate the bias of each arena so that it could be used to ‘correct’ for arena scoring effects on home game fenwick.
I’m thinking that you’d set up a separate model for each team that would regress their fenwich (for and against) against each team with their away-game fenwick against the same team. So for example, for the Leafs you would regress their home fenwick against the bruins, flyers, lightning, etc on their away game fenwick against the bruins, flyers, lightning, etc. That would give you an estimate of how fenwick at the ACC compared to the same team playing in the rest of the league. Then you could repeat the exercise for the fenwick of the teams the Leafs were playing against. Hopefully the estimate of ACC bias would be similar for both the home and away teams (so the counter isn’t systematically boosting/screwing the home team). If they are then you could average them together for an overall ACC bias score. Repeat for the other arenass.
Then you could try to use teams fenwick from home games, and just apply the bias correction to it first. You get the bigger sample size while removing the exogenous variance from arena-specific counting.
On the other hand, that’d be quite a long and involved exercise.
“If we were really sophisticated we could come up with some kind of model that would estimate the bias of each arena so that it could be used to ‘correct’ for arena scoring effects on home game fenwick.”
Gabe Desjardins has actually done something like this in his recent Shot Quality measurement:
http://www.arcticicehockey.com/2011/11/24/2585121/for-your-analysis-enjoyment-individual-shot-quality
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 7:13 PM EST up reply actions
funny that
he’s looking at individual shot quality if he refuses to admit it exists (biases come out occasionaly in the process of these debates – not naming names here).
Delta as a proxy for shot quality has been oft debated… not sure why people refuse to discuss the comparison between shot location and “shot quality” as a repeatable skill. I think Gabe’s done a pretty bang up job historically of indicating who does and doesn’t outshoot their potential shot quality in the past (Kovy, Tanguay, and not much else).
Anyway… I’m sure other’s have things to say on the subject.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 8:44 PM EST up reply actions
oh and
if you’re unclear on the link, the “actual” columns are what they produced and the “shot quality” columns are what you’d expect them to produce.
Obviously some guys outperform their expectations with regularity.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 8:45 PM EST up reply actions
Of interest to Leaf fans
for players with 500+ shots, Clarke MacArthur is tied for 7th amongst NHL forwards with Milan Hejduk and Chris Stewart at a Delta of 2.2.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 11:18 PM EST up reply actions
Colby Armstrong
is 18th amongst NHL forwards with a 1.8 (tied with Briere).
Further down are Connolly and Kulemin at +0.8, Kessel at +0.5, Lupul at +0.2, and Grabovski at 0.0. Every other Leaf forward is in the negatives.
From a shooting perspective that would make our “top 6” MGK, Kessel + Connolly + Armstrong, with Lupul on the fringe. On D we have Franson at +1.3, Liles at +0.1, Phaneuf at 0.0.
Schenn is -0.2, Bozak is at -0.8, Lombardi is at -1.8, Steckel -2.4.
I had to expand it to 200+ shots to find Franson, Schenn, Bozak and Steckel.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 11:27 PM EST up reply actions
I don’t know of a place or a post that has a glossary of these terms used in advanced stats… things like PDO and the significance of the number. Like said in the comments PDO is team sv% plus team sh% but what is a good number to have there? Same can be said with Fenwick or Corsi (on/off, etc.) The only reason I ask or suggest something like this is that I’m sure there is a bunch of us lurkers that would love to join the conversation but cant because we don’t exactly know what is what or what is good or bad.
I’m slowly starting to understand some of this all but for the most part I forget what is a positive stat and what isn’t as well as know what all the acronyms are since there are so many. A glossary of these terms as well as an example of a positive and negative stat would IMO go long ways to developing more discussions on these types of posts. Like I said, having a glossary for stats/advanced – if there isn’t one already available, in one easy location to use as reference to folks new to all this would be awesome to have. I wish I knew all of them otherwise I would write it myself.
"There's been four different Cup winners the last four years, and I got one of them (Anaheim) and it was a fighting team. We're playing it that way regardless." - B. Burke, Toronto Maple Leafs GM
Start here
http://www.arcticicehockey.com/2009/10/9/1078607/frequently-asked-questions-about
And this to learn some mistakes you may make using advanced stats
http://www.kuklaskorner.com/index.php/psh/comments/an_introduction_to_some_corsi_issues/
Ouch these make my head spin… I wish they were in simple-man’s english and not so long… why can’t it be like, for an example: TOI/60 = time on ice/60mins of play = higher number more playing time that player receives. You know simple simple way of explaining it….in any case I got free time today let’s see what I get out of all that. But still thanks for the start.
"There's been four different Cup winners the last four years, and I got one of them (Anaheim) and it was a fighting team. We're playing it that way regardless." - B. Burke, Toronto Maple Leafs GM
Think of corsi as goals +- but using shots directed to your net minus shots directed at your net (and not shots on goals but shots directed so missed shots, hit posts, saves, goals and blocked all count).
Fenwick is argued to be better then corsi and removes blocked shots because a blocked shot is not a quality shot directed to the net
Then you need to add more detail like does a player get easy zone starts (take faceoff in the ozone) or hard starts (take faceoff in dzone).
And consider does a player play against easy competition or hard competition (quality of competition)
And does a player benefit from playing with a strong teammate (quality of teammate)
I think we should start referring to playing defence as “CFC” because the aim is to break down the other teams ozone.
/thank you I’m here all week
by Wan Ihite on Nov 24, 2011 6:10 PM EST up reply actions 1 recs
There is so much wrong in that second article it isn’t even worth looking at. Except maybe the comments where I point out everything that is wrong with it.
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HockeyAnalysis.com - Taking a Deeper Look at the World of Hockey
by HockeyAnalysis on Nov 24, 2011 4:27 PM EST up reply actions
I’ll go through the comments on shooting % again – I liked that the author presents both sides. And I really like the concept of “context” when applying corsi. People want a # like points to access a player and even if tell them you have to be careful when using corsi that way they may do it anyway.
The author has been sold the bill of goods on corsi/fenwick and he has bought into it and he presents a good story, but he isn’t a numbers guy. He hasn’t done the work himself and he is simply spewing out stuff he thinks is true. I mean, his main counter example is based on 8 games of Brendan Morrison when he was playing through an injury. It’s a garbage article.
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HockeyAnalysis.com - Taking a Deeper Look at the World of Hockey
by HockeyAnalysis on Nov 24, 2011 5:44 PM EST up reply actions
Well I haven’t done the work myself and spew stuff I think is true and then again I think very few really have. At any rate, I agree it is not the best introduction for anyone and you raise some good points.
Hey, we all spew stuff we think is true from time to time. My problem is when people spew stuff they think is true and aren’t man enough to admit they are wrong when proven otherwise and instead choose to spew out more nonsensical stuff that they hope will fool you into thinking they know something you don’t. That’s kind of what he does.
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HockeyAnalysis.com - Taking a Deeper Look at the World of Hockey
by HockeyAnalysis on Nov 24, 2011 8:33 PM EST up reply actions
Think of corsi as goals +- but using shots directed to your at the opposition net minus shots directed at your net
Great job
You wrote this in a way that made it fairly easy to understand and really effective. I’ve read about PDO and Fenwick before and understood their significance to an extent, but the way you wrote it made it all really click for me.
by Five Minutes For Fighting on Nov 24, 2011 6:45 PM EST reply actions
Funniest thing
is how in so many sports people clamour about how great Advanced Statistics (Metrics) are, but always have to explain away results that appear anomalous by NOT using statistics. In baseball, which is pretty boring anyway, stat nuts go crazy when teams with the best Metrics miss the playoffs and teams with lousy Metrics, no matter how you look at it, win the World Series, like San Fran.
Still, if people think they have value, more power to them, but they, like String Theory, aren’t predictive at all.
right, so showing why things are they way they are is a waste of time
I guess we should just give up and watch the game without trying to understand it better because that isn’t boring
how insightful
Resident Internet Tough Guy
by JaredFromLondon on Nov 24, 2011 6:58 PM EST up reply actions
Two things
1) It’s absurd to say something isn’t “predictive at all” when it correlates to winning games with a Pearson r of 0.5351 with a two tailed P value of less than 0.0001 (or 1 in 10,000). That is EXTREMELY statistically significant. For those of you that don’t know what I’m talking about, don’t worry about it.
2) String Theory is actually very predictive and is one of the few models we have that can explain the operations of the physical universe in a relatively complete manner. I also have no idea what the hell that has to do with your opinion about Hockey Statistics.
Either way, I’m unclear about what results you’re observing that appear anomalous. The obvious important conclusion to draw here is that PDO values (i.e. Luck) have a major impact on things this early in the season. Saying something isn’t predictive because you aren’t clear how it is doesn’t mean you’re correct.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 24, 2011 8:40 PM EST up reply actions
Now I thought his string theory comment was a “stretch” of an analogy to the heisenberg uncertainty. That is as soon as players and teams become aware of what measure is used to judge or predict their performance – then that awareness begins to introduce uncertainty into the measure itself making it of questionable use.
Also if you argue luck (i.e. probability) is in the quantum world with team skill defining the parameters of the Shrodinger equation of the team, then the outcome of these games are one of the many possible outcome in multiple universes.
Why do people still respond to this guy? He’s trolling. Just ignore him.
The plural of "anecdote" is not "data".
Internet Champ. I'm on Twitter too! - draglikepull
by Draglikepull on Nov 24, 2011 9:14 PM EST up reply actions
He’s my favourite troll.
Drops a bomb then disappears for weeks
No more moral victories, no more excuses. Put up or shut up.
Lebda-free since July 3.
by nhlcheapshot on Nov 25, 2011 5:57 AM EST up reply actions
See I think that we are unfair to trolls, as we often label people as trolls when they’re simply idiots
In summing up, it's the Constitution, it's Mabo, it's justice, it's law, it's the vibe and... No, that's it, it's the vibe. I rest my case
You just need to look at their comment differential, or C+/-, comparing comments made to comments received. Genuine commenters trend towards an even differential, where trolls (depending on kind) usually have extreme values in either direction (positive or negative). Some people argue, though, that you shouldn’t count sarcastic comments, as they usually indicate the loss of possession of a rational argument.
Come get your duds in order...
So it’s a simple matter of applying the Keegler-Berenson Sarcasm Quotient to their C+/-, then?
by DrExcitement on Nov 25, 2011 12:55 PM EST up reply actions
Nonono, you have to look at topic monomania too. Proper trolls will only harp on one topic again and again, whereas a real commenter will move from area to area. An analysis based purely on C+/- that ignores the Geronsky-Blaskovic Topics per Threat index.
Don’t forget the Kidd-Rajasthan-Gudmundsson Apparent Reasonableness Constant.
by DrExcitement on Nov 25, 2011 1:10 PM EST up reply actions
It’s not clear to me that an individual commenter can drive the topic of conversation in a certain direction as much as this would suggest. Do you have data to suggest they might? I imagine you’d have to look over multiple threads, to avoid small sample size issues.
Just because multiple topics tend to correspond to real discussions doesn’t mean that they speak to the individual level of whether someone is a troll.
Come get your duds in order...
Certainly one person can drive a topic, but is it sustainable? My data shows that if you look at the same commenter over multiple different blogs then you can actually get some reliable evidence that they do, so long as you standardize what that topic is to the particular type of blog.
A good proxy is the Cox-HabFan Number, the absolute value of occurrences of “1967” .
This is, of course, affected by the 2011 Season Effect, which is that the CH# is invalid if predicting the number of points Phil Kessel will score this year.
by DrExcitement on Nov 25, 2011 9:37 PM EST up reply actions
You gotta be in a math frame of mind I guess. I promise you you could figure it out if you sat and worked through it patiently enough. Whether you’d WANT to do that is an entirely different question. The pretty reasonable alternative is to enjoy watching this repeatedly instead.
what do you mean “Feel” … LOL .. just kidding.
FLYERROB ! YOU STAY AWESOME FLYERS FANS ! ~ ~ ~ Lori Wilson Gray ~ ~ April 07th 1967 - May 27th 2011 ~ May you rest in Peace ~ I love you and miss you big Sis ! Bob Wilson JR. ~ ~ ~ July 03rd 1944 - November 06th 2011 ~ ~ I love you Dad ! GOD PLEASE GIVE ME THE STRENGTH ! Two Close Family Members passing in 6 months ~ Give me strength !
I’m unconvinced that “They get a lot of shots on goal, and eventually they’ll start going in”, basically the (or at least A) premise for Fenwick. I’m not sure that’s meaningful, unless we also take shot% into account (as HockeyAnalysis suggests).
If I shoot a million times on Toskala, I’m sure he’ll save literally all of them, because I’m lousy and have an inherently lousy sh%. If Kessel shoots at Toskala, I’m sure he’ll save literally none of them because Kessel is the greatest player in the world. So success is, necessarily, about sh% to a significant degree.
I dunno, this sort of exercise just has kind of a “garbage in garbage out” feeling to it for me – and I don’t mean that in a particularly derogatory way, that’s just the expression.
Applying rigorous statistical methods to something that may or may not mean anything significant doesn’t get rid of the inherent “fuzz” that surrounds variables like those in the Corsi or Fenwick numbers. Before we start playing our games with numbers (and I’m actually a fan of playing games with numbers), I’d like to see a more robust correlation of those numbers with actual hockey success. HockeyAnalysis is definitely on the right track, but the R-values I’m seeing aren’t particularly strong for any of the parameters that we’ve talked about here. I’m sure there’s a combination of factors that do produce a more robust correlation, and I’d like to see us talk about these inputs more before we go all cuckoo with applying the statistical methods to anything. Further to that, I’m willing to bet that we’d need a much larger set of inputs than most of us are comfortable dealing with, and we probably need inputs that aren’t even being properly measured yet.
This is all very general and vague, I know, but that’s my way of avoiding sticking my neck out too far and actually suggesting what these more meaningful inputs might be. :))
by DrExcitement on Nov 25, 2011 12:08 PM EST up reply actions
The R values look low to you and high to me. That’s because you’re used to dealing with physical phenomena where you can predict things with stupendous accuracy. You deal with atoms and molecules and physical forces that are all functionally 100% interchangeable (carbon atoms are carbon atoms are carbon atoms), and can be measured with very high precision.
I’m used to dealing with people, who are just inherently unpredictable and chaotic creatures. We have reliable traits like trust, aggression, joy, and materialistic values, but each person’s experience of these things is often a little bit different, and you can’t access them directly, only by self-reports form people who often aren’t 100% knowlegeable about what’s going on in their own heads. You can find reliable effects, but correlations often max out at .3, .4, or .5. if someone gets a correlation of .9 in my line of work it basically means they’ve measured the same thing twice and their result isn’t very interesting. That’s just how people are. It would be nice if we could be more precise but it’s an inherent limitation of dealing with humans.
Hockey stats are going to be closer to my end than your end. They’ll be a bit better because we’re observing a very constrained physical reality in terms of shots, speed, goals, hits, etc, but the complexity of the game is still pretty great.
I disagree, but for the same reasons. It’s a sufficiently complex system that we can treat (and in this discussion as presented, are treating) it as the kind of physical system that SHOULD behave predictably. If we’re treating sh% and Fenwick as equivalent to “how do you feel about that?”, then what are we doing here?
Social studies don’t come to conclusions like “People do THIS”, they conclude “Under certain circumstances, some people tend to do THIS”. Which is fine, and as you say, a necessary qualification for when you’re dealing with messy things like the behaviour of people. But if we’re trying to quantitatively assess the success of a hockey team, is that level of precision good enough?
Well, maybe, I guess. But then let’s not pretend that we can rank the teams and predict firm outcomes based on these models.
by DrExcitement on Nov 25, 2011 12:34 PM EST up reply actions
I think you are underestimating the portion of hockey that is down to psychology. There are certainly physical things we can observe like shot speeds, distances travelled, goalie positions, etc. But players make those shots and position themselves on the ice based on light reflecting off the various objects, being transduced to their visual cortex via their retinas and optic nerves, then being translated constructed into an image of the ice and the other players, run through the brain’s own internal physics engine, and interpreted by what they’ve internalized about hockey and systems. It gets filtered into psychological constructs like open ice, trailing man, zone assignments, pinching, trust in teammates, assessments of opposing player threat, etc. And then that gets translated into signals sent through efferent nerve fibers telling muscles to twitch and move and propel yourself down the ice, try to reach for pucks as they fly past, trying not to kick forward the puck when your’e an offensive player at the goal mouth, etc.
We observe a mechanical physical system, but the decision making units, and the thing which directs all of the individual bodies into action are all psychology. And that’s where you start to get a lot of randomness injected into the system.
OK, fine. But does that mean that shots taken in tied games on the road can predict success in hockey?
Your answer so far has been “it’s a start, and that’s worth something” (right?), which isn’t wrong, but let’s not pretend that Fenwick numbers accurately capture all that psychology in a way that’s better than another input or set of inputs.
by DrExcitement on Nov 25, 2011 12:52 PM EST up reply actions
I’d more characterize my answer as “it’s the best we’ve got, and it’s better than a straight count of points”.
That doesn’t rule out future improvement, but I don’t think anyone has suggested we should
Is it really the best we’ve got?
REALLY?
by DrExcitement on Nov 25, 2011 1:10 PM EST up reply actions
That’s your job, nerd!
Seriously, though, I’ve been saying all along that there isn’t one better thing. It’s a matter of including a really broad range of inputs and iteratively testing them against reality. So I can’t say the answer is A, it’s A+F+K+M+Q+T+V. The trick is weeding out B, C, and all the other less-important factors.
by DrExcitement on Nov 25, 2011 7:59 PM EST up reply actions
In the abstract this is unarguably true. In practice, though, once you get to the NHL level there may be such a big range restriction on people’s true shooting percentages (at least, compared to the dispersion around those means) that you need at least 2 seasons worth of data on a shooter for your numbers on them to become worthwhile.
It’s sort of like how all the studies on GRE scores show that they predict nothing in graduate school performance. People who do well on them do no better than those who performed worse. So are the GRE’s useless? Well maybe, but basically nobody who gets a terrible score on them is admitted to grad school, so all the studies really show is that there’s no difference in expected performance between people who do pretty well on the GRE and people who do REALLY well.
So maybe you and I have a true shooting value of say 10 points (on a completely hypothetical shooting scale), and Kessel has 2000 points, and Corlton Orr has 1900 points. Let’s also say that when you play out this shooting score in actual game situations it has a standard deviation of, say, 200. That means the difference between me and Kessel or Orr will readily and immediately be apparent in a very small amount of time. I’ll be shooting blanks, and they’ll be scoring at a noticeable rate. But it also means that the difference between Kessel and Orr is not readily apparent. In any given couple of games Orr will regularly have a better result than Kessel. It would take observation of a LOT of games before you can reliably see the difference – that doesn’t mean the difference isn’t there, and that it’s not important, just that it takes a while to become apparent. In technical stats jargon you need a big enough n to shrink the standard error (not SD) down smaller than the actual gap in mean skill level.
Agreed. But that’s not really what I’m talking about. I’m just saying that sh% matters, and while the gap between the best NHLer and the worst NHLer isn’t that great (somewhere there is a string of tyke, bantam, midget, all-the-way-up coaches who will tell you with 100% certainty that Brett Lebda is the single greatest hockey player they ever saw), it clearly has an effect on a team’s success as well as a player’s success and therefore belongs in any model that claims to predict success at either of those levels.
So now we’re up to TWO factors. Let’s talk about the others.
by DrExcitement on Nov 25, 2011 12:26 PM EST up reply actions
don’t disagree. There’s just a caveat about how quickly it can be used. There are already posts on this blog about how good the Leafs really are this season based on their Fenwick. You can sorta kinda do that based on this small a sample size with Fenwich. You can’t with sh%. You just have to be aware of that before you try to use the stats in any given situation.
And I don’t disagree with that. Hooray for us!
BUT… while what you say is true, it doesn’t mean that Fenwick is an actually-good predictor of success, or an assessor of “flukey success” vs. “deserved success” (which is what I think we’re actually trying to determine in the first place, basically, right?). Just because it becomes statistically valid before sh% doesn’t mean that it’s more meaningful.
Let’s plug BOTH into a model and see what we get. And then let’s add inputs like TOI (for individual performance) and, I dunno, PK vs PP time (for team performance), and see what we get then. Add some inputs, take others out, test the correlations and let’s get a model that actually accomplishes what it claims to. I still think Fenwick on its own is far too simplistic to give a realistic measure of success.
by DrExcitement on Nov 25, 2011 12:41 PM EST up reply actions
define “good” :)
There’s 2 things here.
1) Can we look at fenwick and say “don’t get too excited by the points, this is a fluke”. You say ‘no’. I say ‘maybe’. The question isn’t whether fenwick is perfect here, it’s just whether it predicts future success BETTER than looking at the compiled points do. If the standings say that Boston suck (which they do), and if the Fenwick scores say that Boston is actually ok, who are you putting your money on for the rest of the season? Because if it’s fenwick, then you can’t dump too hard on the people saying that fenwick shows Boston is underrated (technically they mean it’s “PROBABLY underrated”, but everything is probabilistic, so that gets left out for convenience).
2) Can we do better than Fenwick? Probably yes. And if you can figure out how to do it, and demonstrate that you are right then you too can become a well-known and respected analyst of hockey statistics. Sadly it’s harder than it looks, and the better formula isn’t missing for a want of anyone trying to look. Maybe you can do better. Best of luck with that, and I’ll be excited for you when you can.
1) It’s hard to say in Boston’s case, because I KNOW they’re probably a better team than their start to the season suggested (though they still suck). This is because my brain can take a holistic view of a team in a way that a statistical model can’t – at least a model that doesn’t require en enormous amount of computing power and time. Anyway, I think I can convince myself that if I had to choose between Team X with 48 points and a Road Fenwick (TIED)% of 46 and Team Y with 37 points and a RF(T)% of 53, I’d still probably say that Team X is probably the better team.
2) We can DEFINITELY do better than Fenwick, is exactly my point. Coming up with a new model is not that much harder than it looks, because it looks friggin’ hard! Which is why I’m not doing it. I’ll gladly contribute to a discussion on what inputs need to go into a Grand Unified Model Of Hockey Success, but daaaaamn, girl We need MAD inputs!
by DrExcitement on Nov 25, 2011 1:03 PM EST up reply actions
and until then you’re happy to keep throwing rocks from the sideline ;)
(though I’ll join you throwing them at Boston, because, as you say, they suck).
Well, they’re CONSTRUCTIVE rocks I’m throwing.
by DrExcitement on Nov 25, 2011 9:22 PM EST up reply actions
Here's the problem with saying "sh% matters"
yes it does. Now go and prove it’s a repeatable skill at the team level. Show that teams can increase their SH% on a regular basis… because as far as I’m aware, that evidence is severely lacking.
Fenwick on the other hand? teams can increase that with regularity… because they have more control over the actions that result in them being in possession of the puck… They can’t control the random factors that result in the puck going in the net (or at least not enough of them can to actually IMPROVE that skill set).
Until you show a team can increase it’s shooting percentage, there’s no point in focusing on that aspect, DESPITE it’s increased correlation to winning. Because it’s completely random luck, as far as most of us can tell, at the team level.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 25, 2011 7:43 PM EST up reply actions
Well, the answer to “how do you increase your sh%?” is “take better shots”.
Which is a result of having better shooters on a team, i.e. having a more talented team.
And it’s not outrageous to say that a more talented team (in any objective measure of talent) is going to win more games, and a good reason for that is that the shooters take better shots (i.e., have a higher sh%).
And that’s not far off from “how do you increase your Fenwick”. If you COULD take more uncontested shots, wouldn’t you? And don’t better players have higher Fenwicks?
I’m not saying that Fenwick is useless, or that sh% is the be-all and end-all. I’m just saying that Fenwick on its own doesn’t make much sense as a success predictor, and that it should be combined with more factors (like sh%) in order to be a more inclusive metric.
by DrExcitement on Nov 25, 2011 9:28 PM EST up reply actions
no.
it’s not “take better shots” in fact the whole argument being proposed (by the person whose work we’re discussing) is that he thinks individual players have a superior shot from the same location…. be it due to timing, release, whatever you want to call it. Taking shots from better locations, that aren’t contested, isn’t what he’s discussing.
Shot locations are already tabulated, and there are measurements related to that – which are NOT considered measures of shot quality in the sense David means. Delta SOT would be one such measure, and we have made use of that in the past also… anyway… I have no idea if you’re aware of this stuff or if you’re trying to “constructively” yet “derisively” cast aside things other people have been looking into for a long team (years). If you’re aware of it, I’m not sure why you aren’t just discussing those values. If you aren’t aware of it, do some more reading.
Telling players to “take better shots” on the team level isn’t going to increase your save percentage on the whole, because you can’t just make crappy shooters better shooters. You could ask the shitty guys to NOT shoot, and the good guys to shoot more, but guess what – this is what happens already, so you’re not really going to see a huge difference from team to team, which is WHY this isn’t something you can control at the team level.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 1:46 AM EST up reply actions
team
should read as time… it’s late and I’ve been drinking… but I still don’t think the thread of where you’re going with this stuff is in particular constructive. In fact I’d say it’s more about being deconstructive.
If you’re saying Fenwick has no value – explain why. You’re arguing that it “seems” to have little value to you without really saying what about it implies it’s completely useless.
Saying that the refinements bother you is like saying you don’t see value in narrowing in on measurements of significance.
If I can tell how the greater economy is going to do by looking at the purchasing rates of heavy equipment for manufacturing in cities with populations over 100,000 people, why wouldn’t I do that? I’m excluding a tonne of other information about the economy; including the purchasing rates of heavy equipment for manufacturing in smaller towns, largely because it clouds the picture significantly with other factors that may or may not be useful.
The fact that I’m refining to a smaller data set doesn’t make the information useless. You’re not really articulating WHAT about the refinement you disagree with, aside from the resulting size of the data set. This despite the fact that there are over 4 years worth of data from over 1000 games per season. How is that a small data set to you?
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 1:52 AM EST up reply actions
I’m not saying it has no value, and I never said it was completely useless. Sober up and stop putting words in my mouth.
I AM saying that by itself, the number of uncontested shots in road games with the score tied does not accurately lead to a prediction of a team’s success. R values of about 0.5 aren’t encouraging.
Is it meaningless? No, it’s a useful metric. But it’s one of many, and if you’re going to actually try to make assertive statements about predicting future success, you need more inputs.
by DrExcitement on Nov 26, 2011 3:12 AM EST up reply actions
That’s right, but sh% is also diagnostic of a team’s talent, AS IS Fenwick. I’m not saying that you can make your players take better shots and thus boost your team’s sh%, any more than you can tell your players to take more uncontested shots on goal and thus boost their Fenwick number. But teams with high sh% (and high Fenwick) can be considered better teams, because they’ve got more talented players that take more and better shots.
The way you improve your team’s numbers – both of them – is not to make your players better, it’s to get better players.
by DrExcitement on Nov 26, 2011 3:09 AM EST up reply actions
If I shoot a million times on Toskala, I’m sure he’ll save literally all of them
But why are you shooting beach balls instead of pucks?
Flugenweb, space code, twit zone, ass mode, check ze tweets.
We were shooting pucks. Just not, apparently, from far enough away.
by Wan Ihite on Nov 25, 2011 1:39 PM EST up reply actions 1 recs
The data shows that Fenwick (or some other chosen measure) correlate to wins.
And to say that the measure (Fenwick) is a cause of wins is another level of abstraction.
From what I have seen, the only thing we know is that they tend to co-relate but don’t know which of these two causes the other, or if a third factor is causing both winning and fenwick or even if the co-relation is entirely coincidental as unlikely as the result show but still a possibility in world of probability.
Sure. Even though one can say that “Good teams have high [Fenwick/sh%/plus-minus/whatever”, are these symptoms of being a good team (these are things that result from playing hockey well), or are they the disease (you need to do this in order to play hockey well)?
Sorting that out, as I’ve been saying a lot here, is going to have to rely on empirical observations of iteratively-tweaked variables until we find something that best describes the “disease” of a winning hockey team.
by DrExcitement on Nov 25, 2011 9:33 PM EST up reply actions
Again
you’re implying nobody has DONE what you’re describing. What is leading you to this conclusion?
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 1:53 AM EST up reply actions
Because a Grand Unified Predictive Model For Hockey Success doesn’t exist yet.
I’m not saying no one’s put any work into it – clearly many people, including you, have.
But there are so many degrees of freedom inherent in describing team success (and even more in determining player success) that any model which is going to have a realistic outcome is going to have to be comprehensive enough that it will require a huge number of variables, each weighted differently, iteratively tested against reality. That’s a lot of computing power and time.
A really simple but important question: How do you determine the uncertainties in your model? I don’t see any mention of this at all anywhere, and if you’re going to talk about “advanced stats”, neglecting uncertainties is a major crime.
Look, I don’t mean to insult you personally at all. You’re willing to do the work that I’m clearly not. But really, don’t conclude a post with “Let me know if you have any questions and feel free to debate the worth or value of the stat – I know some of you want to” if you don’t want anybody to actually do that.
by DrExcitement on Nov 26, 2011 3:32 AM EST up reply actions
Valid
and yeah, apologies for being overly defensive last night.
I appreciate the constructive criticism, I just think there’s a bit of an information divide at work here.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 8:18 PM EST up reply actions
Also...
How about the effect of “Impact Players”? Players who can not only single-handedly change the outcome of a game, but do it often enough to affect a team’s performance over a season?
Because of course different players require different parameters to predict their impact. To figure out how much Kessel’s going to contribute, you need to think about his TOI, sh%, sh#, time on PP, that kind of thing. Whereas Chara’s impact is best measured in terms of hits, blocked shots, TOI, time on PK, assists, stuff like that. And then the resulting package of THAT has to get somehow rolled into a team’s predictive algorithm. And many teams have more than one such player.
Which means that every team has its own player variables to work in, which of course complicates things enormously, but at least leads to a more comprehensive answer to the problem of “different teams play differently”. A good predictor should work just as well for the ’90s Devils as the 2010 Capitals.
PP
and PK are far more random events. SH% is more random.
I feel like you’re either completely missing the point, or you just don’t care.
"Success is the ability to go from one failure to another with no loss of enthusiasm."
- Sir Winston Churchill
I'm pretty sure he's talking about the Leafs.
by Steve Burtch on Nov 26, 2011 2:05 AM EST up reply actions
Yeah, I agree.
This is just an idea about how to more fully describe a team’s play and their chances of success. Different teams play differently, and a significant part of that is that they play to their strengths, and a big part of THAT is that the effect of star players. But star players play differently, so what factors go into how we assign a value to these players?
Yes, PP and PK certainly aren’t the best factors to use. I’m just throwing out a wide range of possible factors to include in that sort of “bigger factor”.
by DrExcitement on Nov 26, 2011 3:18 AM EST up reply actions

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