Apr 192012
 

Prior to the season Gabe Desjardins and I had a conversation over at MC79hockey.com where I predicted several players would combine for a 5v5 on-ice shooting percentage above 10.0% while league average is just shy of 8.0%.  I documented this in a post prior to the season.  In short, I predicted the following:

  • Crosby, Gaborik, Ryan, St. Louis, H. Sedin, Toews, Heatley, Tanguay, Datsyuk, and Nathan Horton will have a combined on-ice shooting percentage above 10.0%
  • Only two of those 10 players will have an on-ice shooting percentage below 9.5%

So, how did my prediction fair?  The following table tells all.

Player GF SF SH%
SIDNEY CROSBY 31 198 15.66%
MARTIN ST._LOUIS 74 601 12.31%
ALEX TANGUAY 43 371 11.59%
MARIAN GABORIK 57 582 9.79%
JONATHAN TOEWS 51 525 9.71%
NATHAN HORTON 34 359 9.47%
HENRIK SEDIN 62 655 9.47%
BOBBY RYAN 52 552 9.42%
PAVEL DATSYUK 50 573 8.73%
DANY HEATLEY 42 611 6.87%
Totals 496 5027 9.87%

Well, technically neither of my predictions came true.  Only 5 players had on-ice shooting percentages above 9.5% and as a group they did not maintain a shooting percentage above 10.0%.  That said, my prediction wasn’t all that far off.  8 of the 10 players had an on-ice shooting percentage above 9.42% and as a group they had an on-ice shooting percentage of 9.87%.  If Crosby was healthy for most of the season or the Minnesota Wild didn’t suck so bad the group would have reached the 10.0% mark.  So, when all is said and done, while technically my predictions didn’t come perfectly true, the intent of the prediction did.  Shooting percentage is a talent, is maintainable, and can be used as a predictor of future performance.

I now have 5 years of on-ice data on stats.hockeyanalysis.com so I thought I would take a look at how sustainable shooting percentage is using that data.  To do this I took all forwards with 350 minutes of 5v5 zone start adjusted ice time in each of the past 5 years and took the first 3 years of the data (2007-08 through 2009-10) to predict the final 2 years of data (2010-11 and 2011-12).  This means we used at least 1050 minutes of data over 3 seasons to predict at least 700 minutes of data over 2 seasons.  The following chart shows the results for on-ice shooting percentage.

Clearly there is some persistence in on-ice shooting percentage.  How does this compare to something like fenwick for rates (using FF20 – Fenwick For per 20 minutes).

Ok, so FF20 seems to be more persistent, but that doesn’t take away from the fact that shooting percentage is persistent and a reasonable predictor of future shooting percentage.  (FYI, the guy out on his own in the upper left is Kyle Wellwood)

The real question is, are either of them any good at predicting future goal scoring rates (GF20 – goals for per 20 minutes) because really, goals are ultimately what matters in hockey.

Ok, so both on-ice shooting percentage and on-ice fenwick for rates are somewhat reasonable predictors of future on-ice goal for rates with a slight advantage to on-ice shooting percentage (sorry, just had to point that out).  This is not inconsistent with what I  found a year ago when I used 4 years of data to calculate 2 year vs 2 year correlations.

Of course, I would never suggest we use shooting percentage as a player evaluation tool, just as I don’t suggest we use fenwick as a player evaluation tool.  Both are sustainable, both can be used as predictors of future success, and both are true player skills, but the best predictor of future goal scoring is past goal scoring, as evidenced by the following chart.

That is pretty clear evidence that goal rates are the best predictor of future goal rates and thus, in my opinion anyway, the best player evaluation tool.  Yes, there are still sample size issues with using goal rates for less than a full seasons worth of data, but for all those players where we have multiple seasons worth of data (or at least one full season with >~750 minutes of ice time) for, using anything other than goals as your player evaluation tool will potentially lead to less reliable and less accurate player evaluations.

As for the defensive side of the game, I have not found a single reasonably good predictor of future goals against rates, regardless of whether I look at corsi, fenwick, goals, shooting percentage or anything else.  This isn’t to suggest that players can’t influence defense, because I believe they can, but rather that there are too many other factors that I haven’t figured out how to isolate and remove from the equation.  Most important is the goalie and I feel the most difficult question to answer in hockey statistics is how to separate the goalie from the defenders. Plus, I believe there are far fewer players that truly focus on defense and thus goals against is largely driven by the opposition.

Note:  I won’t make any promises but my intention is to make this my last post on the subject of sustainability of on-ice shooting percentage and the benefit of using a goal based player analysis over a corsi/fenwick based analysis.  For all those who still fail to realize goals matter more than shots or shot attempts there is nothing more I can say.  All the evidence is above or in numerous other posts here at hockeyanalysis.com.  On-ice shooting percentage is a true player talent that is both sustainable and a viable predictor of future performance at least on par with fenwick rates.  If you choose to ignore reality from this point forward, it is at your own peril.