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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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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 Presentation Transcript

  • DIGR: A Defense Independent Rating of NHL Goaltenders using Spatially Smoothed Save Percentage Maps Michael E. Schuckers* St. Lawrence UniversityStatistical Sports Consultingschuckers@stlawu.edu  
    *Thanks to Chris Wells, Ken Krzywicki, Dan Downs, Dennis Lock, Matt Generous
  • 2009-10 Save Percentage
    Goalie Gi Team Pts
    Brodeur (NJD) 0.916 103*
    Luongo (VAN) 0.913 103*
    Turco (DAL) 0.913 88
    Ward (CAR) 0.916 80
    * Made Stanley Cup playoffs
  • Gi=
    Problem:
    Each goalie faces different distribution of shots
    Goal of this paper
    Find statistical methodology to allow comparison
    Save Percentage
  • Rethinking Save Percentage
    s=shot type
    Pi(s)
    Ri(s)
    Xi(s) = Number of saves by goalie ion shots of type s
    Ti(s) = Total number of shots faced by goalie ion shots of type s
    Pi(s) = performance (save percentage) of goalie ion shot type s
    Ri(s) = percent/rate of all shots for goalie ithat were of type s
  • Rethinking Save Percentage
    Save Percentage
    Convert to`R(s) the league average distribution of shots faced
  • Data
    Downloaded from ESPN.com GameCast
    Every NHL regular season game 09-10
    Goalie
    (x,y) location of ( n= )74300 shots
    Opponents strength
    Shot Type
    Location*
    Home/Away Team
    *Madison Square Garden is a statistical nightmare in hockey
  • Shots
    s=(x-coord, y-coord, shot type, strength)
    All shots converted to single offensive zone
    Shot types
    Backhand, Deflection, Slap, Snap, Tip-in, Wrap and Wrist
    Strength
    Even, Power Play, Shorthanded
  • Spatial Smoothing
    Use LOWESS* (locally weighted scatterplotsmoothing)
    Nonparametric (no specific model)
    One map for each strength x shot type (21)
    Use all shots for given shot type (total weight 30)
    *Using loess in R
  • Why smooth? Luongo vs. Distance
  • Ryan Miller/ Slap Shots/ Even Strength
  • Ryan Miller/Slap Shot
    Even Strength
    Power Play
    Shorthanded
  • Tomas Vokoun/Slap Shot
    Even Strength
    Power Play
    Shorthanded
  • NiklasBackstrom/Slap Shot
    Power Play
    Even Strength
    Shorthanded
  • Rethinking Save Percentage
    Save Percentage
    Shot Quality Adjusted
    Save Percentage
    (E. g. Krzywicki (2010))
    Defense Independent
    Goalie Rating (DIGR)
  • Application
    49 goalies >600 shots faced in 2009-10 Regular Season
    Each shot (n=74300), each goalie
    predicted goal probability using smoothed maps
    Calculated DIGR
  • Results: Top 10
    0.01 = 20 goals for a goalie facing 2000 shots
  • Results: Other Notables
    0.01 = 20 goals for a goalie facing 2000 shots
  • Results
    Big* Winners(DIGR - Save Pct >> 0)
    Smith(TBL), Roloson (NYI), Huet (CHI),
    Pavelec (ATL), Varlamov (WSH), Biron (NYI), Theodore (WSH), Leclaire (OTT),
    Toskala (TOR, CGY)
    Big* Losers (DIGR - Save Pct << 0)
    Rask (BOS), Howard (DET), Thomas (BOS)
    Big means > 0.0075 OR 15 goals on 2000 shots
  • Results (2000 shots using`R(s))
    Rank PlayerDIGR Goals
    1 Miller(BUF) 143

    11Hedberg(ATL) 162
    ….
    21 Anderson (COL) 173

    31 Ellis (NSH) 177

    41 Huet(CHI) 191

    49 Toskala(TOR, CGY) 206
    DPts=0.35*GoalDiff
    6.7
    3.9
    1.4
    4.9
    5.0
    19
    11
    4
    14
    15
  • Discussion
    Average season performance
    Standard Errors (Bootstrap)
    Shot target (holes 1 to 5)
    Injuries (e.g. Tim Thomas)
    Extension G*ij=SsPi(s) Rj(s)
  • Turco takes Niemi’s shots
    June 2010 Blackhawks win Stanley Cup
    Need Cap Space
    Fail to resign Niemi and sign Turco
    Saving $1.45 million
    GiGi*(DIGR)
    Niemi(CHI) 0.915 0.922
    Turco (DAL) 0.912 0.910
    G*ij=SsPi(s)Rj(s) (i=Turco, j = Niemi) = 0.903
  • Turco takes Niemi’s shots
    Turco G*ij = 0.903 vsNiemi G*jj = 0.915
    What’s the cost?
    Turco on pace to face about 1000 shots in 2010-11
    1000 shots *(0.012) = 12 goals
    12 goal *0.35 = 4.2 pts
    Turco Save Pct (2010-11) = 0.897
  • DIGR vs. ‘09-’10 Salary
  • Summary
    DIGR: Defense Independent Goalie Rating
    Three innovations
    - Spatial smoothing maps
    - Goalie ratings on comparable shot distribution
    - Mathematical framework
  • Thank You!schuckers@stlawu.edu