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DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps
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DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps

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2011 5th MIT Sloan Sports Analytics Conference

2011 5th MIT Sloan Sports Analytics Conference

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  • 1. DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps Michael E. Schuckers* St. Lawrence UniversityStatistical Sports Consultingschuckers@stlawu.edu  <br />*Thanks to Chris Wells, Ken Krzywicki, Dan Downs, Dennis Lock, Matt Generous<br />
  • 2. 2009-10 Save Percentage<br />Goalie Gi Team Pts<br />Brodeur (NJD) 0.916 103*<br />Luongo (VAN) 0.913 103*<br />Turco (DAL) 0.913 88<br />Ward (CAR) 0.916 80<br />* Made Stanley Cup playoffs<br />
  • 3. Gi=<br />Problem:<br />Each goalie faces different distribution of shots <br />Goal of this paper<br />Find statistical methodology to allow comparison<br />Save Percentage<br />
  • 4. Rethinking Save Percentage<br />s=shot type<br />Pi(s)<br />Ri(s)<br />Xi(s) = Number of saves by goalie ion shots of type s<br />Ti(s) = Total number of shots faced by goalie ion shots of type s<br />Pi(s) = performance (save percentage) of goalie ion shot type s<br />Ri(s) = percent/rate of all shots for goalie ithat were of type s<br />
  • 5. Rethinking Save Percentage<br />Save Percentage<br />Convert to`R(s) the league average distribution of shots faced<br />
  • 6. Data<br />Downloaded from ESPN.com GameCast<br />Every NHL regular season game 09-10<br /> Goalie <br /> (x,y) location of ( n= )74300 shots<br /> Opponents strength<br /> Shot Type<br /> Location*<br /> Home/Away Team<br />*Madison Square Garden is a statistical nightmare in hockey<br />
  • 7. Shots<br />s=(x-coord, y-coord, shot type, strength)<br />All shots converted to single offensive zone<br />Shot types <br />Backhand, Deflection, Slap, Snap, Tip-in, Wrap and Wrist<br />Strength<br />Even, Power Play, Shorthanded<br />
  • 8. Spatial Smoothing<br />Use LOWESS* (locally weighted scatterplotsmoothing) <br />Nonparametric (no specific model)<br />One map for each strength x shot type (21)<br />Use all shots for given shot type (total weight 30)<br />*Using loess in R<br />
  • 9. Why smooth? Luongo vs. Distance<br />
  • 10. Ryan Miller/ Slap Shots/ Even Strength<br />
  • 11. Ryan Miller/Slap Shot<br />Even Strength<br />Power Play<br />Shorthanded<br />
  • 12. Tomas Vokoun/Slap Shot<br />Even Strength<br />Power Play<br />Shorthanded<br />
  • 13. NiklasBackstrom/Slap Shot<br />Power Play<br />Even Strength<br />Shorthanded<br />
  • 14. Rethinking Save Percentage<br />Save Percentage<br />Shot Quality Adjusted <br />Save Percentage <br />(E. g. Krzywicki (2010))<br />Defense Independent<br />Goalie Rating (DIGR)<br />
  • 15. Application<br />49 goalies &gt;600 shots faced in 2009-10 Regular Season<br />Each shot (n=74300), each goalie<br /> predicted goal probability using smoothed maps<br />Calculated DIGR<br />
  • 16. Results: Top 10<br />0.01 = 20 goals for a goalie facing 2000 shots<br />
  • 17. Results: Other Notables<br />0.01 = 20 goals for a goalie facing 2000 shots<br />
  • 18. Results<br />Big* Winners(DIGR - Save Pct &gt;&gt; 0)<br /> Smith(TBL), Roloson (NYI), Huet (CHI), <br />Pavelec (ATL), Varlamov (WSH), Biron (NYI), Theodore (WSH), Leclaire (OTT), <br />Toskala (TOR, CGY) <br />Big* Losers (DIGR - Save Pct &lt;&lt; 0)<br /> Rask (BOS), Howard (DET), Thomas (BOS)<br />Big means &gt; 0.0075 OR 15 goals on 2000 shots<br />
  • 19. Results (2000 shots using`R(s))<br />Rank PlayerDIGR Goals<br />1 Miller(BUF) 143<br />…<br />11Hedberg(ATL) 162<br />….<br />21 Anderson (COL) 173<br />…<br />31 Ellis (NSH) 177<br />…<br />41 Huet(CHI) 191<br />…<br />49 Toskala(TOR, CGY) 206<br />DPts=0.35*GoalDiff<br />6.7<br />3.9<br />1.4<br />4.9<br />5.0<br />19<br />11<br />4<br />14<br />15<br />
  • 20. Discussion<br />Average season performance<br />Standard Errors (Bootstrap)<br />Shot target (holes 1 to 5)<br />Injuries (e.g. Tim Thomas)<br />Extension G*ij=SsPi(s) Rj(s)<br />
  • 21. Turco takes Niemi’s shots<br />June 2010 Blackhawks win Stanley Cup<br /> Need Cap Space<br /> Fail to resign Niemi and sign Turco<br /> Saving $1.45 million <br />GiGi*(DIGR)<br />Niemi(CHI) 0.915 0.922<br />Turco (DAL) 0.912 0.910<br />G*ij=SsPi(s)Rj(s) (i=Turco, j = Niemi) = 0.903<br />
  • 22. Turco takes Niemi’s shots<br />Turco G*ij = 0.903 vsNiemi G*jj = 0.915<br />What’s the cost?<br />Turco on pace to face about 1000 shots in 2010-11<br />1000 shots *(0.012) = 12 goals <br />12 goal *0.35 = 4.2 pts<br />Turco Save Pct (2010-11) = 0.897<br />
  • 23. DIGR vs. ‘09-’10 Salary<br />
  • 24. Summary<br />DIGR: Defense Independent Goalie Rating<br />Three innovations<br />- Spatial smoothing maps<br />- Goalie ratings on comparable shot distribution<br />- Mathematical framework <br />
  • 25. Thank You!schuckers@stlawu.edu  <br />

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