Hockey Sabermetrics: Project Helium “Carbon Block” – Analysis of Forwards
For my third Project Helium hockey sabermetrics study of “Carbon Block”, I am going to compare and contrast different types of forwards.
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Since I have used nothing but defensemen for my first two studies, the outcome of this one may have a much greater difference in results from player-to-player.
I will use the same seasons (2013-14 and 2014-15) as I did before. However, I will be using the average of both years, instead of tracking both seasons. The players will be ranked 7-1, with 7 as the worst score and 1 as the best (lower score is better).
Carbon Block formula: Blocked Shots+Takeaways/Time on ice=x
7. Daniel Sedin (playmaker): average score of 35.69
Daniel Sedin’s game has more to do with setting up his line mates for goals than scoring then himself. Looking at his stats, his assists far outweigh goals scored (20 goals, 56 assists in 2014-15). Sedin also is not the type of player that blocks many shots – but, instead plays a strong positional game.
6. Henrik Sedin (playmaker): average score of 31.02
I decided to analyze both Sedin twins to see if there would be much of a difference in their Carbon Block score. It turns out that there wasn’t, even though Daniel’s higher score (worse, actually) was over 40 and Henrik’s never got above 36. I think the fact that both are finesse players (playmakers) makes them less likely to go into the dirty areas, which can severely effect a player’s carbon block score.
5. Phil Kessel (pure scorer/sniper): average score of 29.04
Considering the fact that Kessel’s job is to score, not block shots, it makes sense that he doesn’t score particularly well in Carbon Block. The most blocked shots or takeaways he had in either year was 37 (takeaways in 2013), which means he wasn’t going to put up a high score. I don’t think his teammates cared much though, as he put up over 60 points both seasons.
Related Story: Project Helium: Carbon Block - Erik Karlsson vs Drew Doughty
4. Patrick Kane (playmaker/two-way forward): average score of 23.56
Kane is one of the best all-around forwards in the game, however for the two seasons I used for the study he never played more than 69 games (2013-14). That right there means his ice time would be limited, not to mention his other statistics. His score is probably fairly accurate, however it will be interesting to see what his score will be for 2015-16. Not to mention the fact that he never score more than 30 goals in either season (Kane did score 29 in 2013-14)
3. Patrice Bergeron (two-way forward): average score of 13.58
Now we are on our way to forwards that focus on defense a bit more. Bergeron blocked around 60 shots both seasons, including an average of around 50 takeaways each year. Not to mention he will provide offense, considering the fact that he can score 30 goals. His score is closer to what some of the defenseman scored in Carbon Block
2. Ryan Getzlaf (power forward): average score of 11.01
Considering the fact that Getzlaf is a power forward, he will be in front of the net, in the dirty area, and sacrificing his body a lot of the time. If a player isn’t afraid to get in front of the net offensively, it is likely that he isn’t afraid to block shots as well. Getzlaf blocked nearly 100 shots in 2014-15 (95 total), meaning that he will provide defense for whomever he plays for. Not to mention he’s an offensive threat as well.
1. Mark Stone (hidden value): score of 9.02 (2014-15)
I only used 2014-15 for Stone due to the fact that he didn’t play enough minutes the previous season (275:02). Stone will block shots, but has a great ability to take the puck away from the opposition (98 in 2014-15), which improves his Carbon Block score drastically. Stone will also help out offensively (26 G, 38 A in ‘14-15), he adds a value to the defensive zone that many forwards don’t.
Next: Project Helium: Carbon Block - Duncan Keith vs Shea Weber
Overall, I find value in the fact that the more physical/defensive oriented a forward is the better his Carbon Block score is. Given the fact that it won’t be perfect every time, I think it will be intriguing to see if over the course of the studies run on this formula if this theory runs true. Stick around to find out.
Sources: www.nhl.com www.foxsports.com