Editor's Note: clrkaitken's been working on some interesting calculations about Phil Kessel and his comparables in the NHL. The numbers paint quite the picture.
Long story short...
In the aftermath discussion of the announced Kessel trade, "say plan the parade one more time" mused about how Phil Kessel's season stacked up against other top scorers in the league last year.
Over the past few hours, I've pored over the stats of the top scoreres from the 2008-09 season, and created a huge spreadsheet that served to try and accurately compare Kessel's season, apples to apples, to those of the league's top guns.
Seeing how it's past midnight, and I'm barely coherent from the double-barrelled shotgun of the Kessel trade reaction and doing this for the past two hours, I'll put this up for now, and then tomorrow I'll post my findings and go into detail about how our new boy stacks up. The comparative players might put a new spin on the trade for some people.
First off, allow me to apologize for sleep and real-life getting in the way of me finishing this. Hopefully much like the Kessel deal itself, this will be worth it once it finally is ready to go.
After compiling all of the relevant statistics from NHL.com, I've tried to determine who is a comparable offensive player to Phil Kessel. This was primarily based on three statistics:
G/A Ratio - A measure of the number of goals a player scored for every assist. For instance, Phil Kessel's G/A ratio was 1.5 last season. For every 3 goals, Kessel would register 2 assists.
GPG - A measure of the average number of goals a player scored in each game.
PPG - A measure of the average number of points a player scored in each game.
To be considered "comparable", a player needed to have a number that is within 25% of Kessel's statistics. 10 players had comparable numbers to Kessel for those three stats.
Jeff Carter, Eric Staal, Marian Hossa, Thomas Vanek, Dany Heatley, Patrick Marleau, Loui Erikkson, Johan Franzen, Jason Arnott, Alexander Frolov
First, let's put everyone on equal terms. Using the GPG and PPG for each individual, I've projected what we could expect their stats to look like if they all played 70 games, which is what Kessel played last season.
Kessel 70GP 34-26-60
Carter 39-33-72
Staal 34-30-64
Hossa 38-29-67
Vanek 38-23-61
Heatley 33-28-61
Marleau 35-30-65
Eriksson 31-23-54
Franzen 34-24-58
Arnott 36-25-61
Frolov 29-25-54
Based on 70 games, Kessel would have been outperformed by Carter, Staal, Hossa, and Marleau. He would have been superior to Eriksson and Frolov, and pretty much in-line with Vanek, Heatley, Franzen and Arnott However, these statistics aren't entirely representative, because almost everybody played a significantly higher number of minutes than Kessel did. Kessel played about 16 and a half minutes a night, while most played 18 or 19, and some up to 21 minutes a night.
Let's factor in another statistic that I calculated from the information available, ATOI/G. The calculation determines the approximate amount of time a player is on the ice before scoring a goal. For instance, based on 16:33 minutes a night, and 70 games, and 36 goals, Kessel scored a goal every 32:11 of ice time. This figure is significantly better than all of the comparitave players (except Hossa & Vanek).Let`s adjust everybody`s 70 game statistics, to simulate that they all played an average of 16:33 a night, statistics that are exactly identical to Kessel`s.
Kessel 70GP 34-26-60
Carter 32-26-58
Staal 27-23-50
Hossa 35-28-63
Vanek 37-22-59
Heatley 27-24-51
Marleau 27-24-51
Eriksson 26-19-45
Franzen 31-22-53
Arnott 31-23-54
Frolov 24-21-45
Now, all of a sudden Kessel's production seems very favourable. If you take away some of the additional minutes these guys played, suddenly their production starts to pale in comparison to Kessel, and he's right on line with guys like Jeff Carter, Marian Hossa, and Tomas Vanek, people who are considered elite goal scorers in the league.
Now here's where the naysayers start to talk about "the Savard effect"; primarily, the fact that Phil Kessel's production was largely dependent on the quality of his teammates. So let's look at the Quality of Competition and Quality of Teammate statistics from Behindthenet.ca for these players.
Kessel QOC 0.014 QOT 0.225
Carter 0.039 0.039
Staal 0.053 (0.037)
Hossa 0.023 0.481
Vanek 0.016 0.032
Heatley 0.039 0.003
Marleau 0.018 0.334
Eriksson 0.044 (0.115)
Franzen 0.057 0.235
Arnott (0.002) 0.132
Frolov 0.037 0.013
So, there may be a little bit of truth to the effect that Boston's great squad had on his numbers.But two people's numbers jumped out at me; Marelau and Hossa.
Patrick Marleau had a greater QOT, and a pretty comparable QOC. Given the same amount of ice time, we would have expected him to score 10 points less than Kessel. Marleau was also 29 last year, and making $6.3M.
Marian Hossa, however, played against stiffer competition, but was surrounded by immense talent in Detroit. If we project similar ice time to Kessel, his production would likely be consistent with Kessel's. He turned 30 last season, and Chicago has seen fit to pay him $7.9 million for the next seven years (cap hit being $5.275M because of the 12 year contract).
I'm not suggesting this is in any way conclusive, and it makes a ton of assumptions. But I think what I've managed to demonstrate is that the raw numbers for a lot of these guys are masked by the fact that they log pretty high minutes for a forward. Playing far less minutes, Kessel was a significantly more effecient player than all of these "elite" scorers. The other thing is that most of these players are already in their prime, while one could argue that at 21, Kessel hasn't even reached his yet.
If Kessel can click with one of our good young centres (Grabovski, Kadri, hell, maybe even Stajan) and match his breakout season, I think that $5.4 million might be a downright bargain.
Below, is the spreadsheet I compiled to do my initial analysis.
| Player | GP | G | A | Pts | G/A | GPG | PPG | ATOI | ATOI/G |
| Phil Kessel | 70 | 36 | 24 | 60 | 1.50 | 0.514 | 0.857 | 16.55 | 32.18 |
| Alex Ovechkin | 79 | 56 | 54 | 110 | 1.04 | 0.709 | 1.392 | 23 | 32.45 |
| Jeff Carter | 82 | 46 | 38 | 84 | 1.21 | 0.561 | 1.024 | 20.57 | 36.67 |
| Zach Parise | 82 | 45 | 49 | 94 | 0.92 | 0.549 | 1.146 | 18.75 | 34.17 |
| Ilya Kovalchuk | 78 | 43 | 48 | 91 | 0.90 | 0.551 | 1.167 | 21.8 | 39.54 |
| Rick Nash | 78 | 40 | 39 | 79 | 1.03 | 0.513 | 1.013 | 21.15 | 41.24 |
| Eric Staal | 82 | 40 | 35 | 75 | 1.14 | 0.488 | 0.915 | 21.03 | 43.11 |
| Marian Hossa | 74 | 40 | 31 | 71 | 1.29 | 0.541 | 0.959 | 17.78 | 32.89 |
| Thomas Vanek | 73 | 40 | 24 | 64 | 1.67 | 0.548 | 0.877 | 17.18 | 31.35 |
| Dany Heatley | 82 | 39 | 33 | 72 | 1.18 | 0.476 | 0.878 | 20.1 | 42.26 |
| Mike Cammalleri | 81 | 39 | 43 | 82 | 0.91 | 0.481 | 1.012 | 17.55 | 36.45 |
| Patrick Marleau | 76 | 38 | 33 | 71 | 1.15 | 0.500 | 0.934 | 21.35 | 42.70 |
| Loui Eriksson | 82 | 36 | 27 | 63 | 1.33 | 0.439 | 0.768 | 19.82 | 45.15 |
| Evgeni Malkin | 82 | 35 | 78 | 113 | 0.45 | 0.427 | 1.378 | 22.52 | 52.76 |
| Jarome Iginla | 82 | 35 | 54 | 89 | 0.65 | 0.427 | 1.085 | 21.6 | 50.61 |
| Jonathan Toews | 82 | 34 | 35 | 69 | 0.97 | 0.415 | 0.841 | 18.62 | 44.91 |
| Simon Gagne | 79 | 34 | 40 | 74 | 0.85 | 0.430 | 0.937 | 19.02 | 44.19 |
| Johan Franzen | 71 | 34 | 25 | 59 | 1.36 | 0.479 | 0.831 | 18.1 | 37.80 |
| Alex Semin | 62 | 34 | 45 | 79 | 0.76 | 0.548 | 1.274 | 19.23 | 35.07 |
| Brad Boyes | 82 | 33 | 39 | 72 | 0.85 | 0.402 | 0.878 | 19.13 | 47.54 |
| Sidney Crosby | 77 | 33 | 70 | 103 | 0.47 | 0.429 | 1.338 | 21.93 | 51.17 |
| Jason Arnott | 65 | 33 | 24 | 57 | 1.38 | 0.508 | 0.877 | 18.9 | 37.23 |
| Alexander Frolov | 77 | 32 | 27 | 59 | 1.19 | 0.416 | 0.766 | 19.92 | 47.93 |
| Pavel Datsyuk | 81 | 32 | 65 | 97 | 0.49 | 0.395 | 1.198 | 19.2 | 48.60 |
| Corey Perry | 78 | 32 | 40 | 72 | 0.80 | 0.410 | 0.923 | 18.6 | 45.34 |
| Jason Spezza | 82 | 32 | 41 | 73 | 0.78 | 0.390 | 0.890 | 19.68 | 50.43 |
| Shane Doan | 82 | 31 | 42 | 73 | 0.74 | 0.378 | 0.890 | 20.23 | 53.51 |
| Daniel Sedin | 82 | 31 | 51 | 82 | 0.61 | 0.378 | 1.000 | 18.78 | 49.68 |
| Patrick Elias | 77 | 31 | 47 | 78 | 0.66 | 0.403 | 1.013 | 18.57 | 46.13 |


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