Total Hockey Rating (THoR) - MIT Sloan Sports Analytics Conference

Total Hockey Rating (THoR): A comprehensive statistical rating of National Hockey

League forwards and defensemen based upon

© 2013 Michael Schuckers & James Curro

St. Lawrence University, Statistical Sports Consulting LLC

& Iowa State University

Introduction

• Hockey Metrics

– Traditional

• +/-, Pts

– Advanced

• CorsiRel (Desjardins), GVT (Awad), DeltaSOT (Awad),

• Expected Goals +/- (Macdonald)

Schuckers&Curro (c) 2013 2

Goals

• THoR

– Value every play on the ice

– Account for Teammates (QoT)

– Account for Opponents (QoC)

– Account for Zone Starts (ZS)

– Account for Home Ice


Data


• Real Time Scoring System (RTSS)

– NHL generated

– Recording (Shots, Goals, Misses, Blocked Shots, Hits, Faceoffs, End of Period, Stoppage)

– Players on the ice for both teams

– Shot Location x,y coordinates

Data


• Real Time Scoring System (RTSS)

– Rich, not great quality

– Known issues with X,Y coordinates (esp. MSG)

– Giveaways and Takeaways Biased

– Questions about Faceoffs (~5%), Hits

– Rink to rink variability

Adjustments

CDF Adjustment for X, Y coordinates

Start with shot recorded at X-coord t at rink R,

Then

t’= FX-1( FR(t) – (FRA(t)-FA(t) )),

FX is cdf for all X coordinates

FR is the cdf’s for x coordinates for rink R

FRA is the cdf’s for all shots taken by the away

FA is the cdf’s of x for all away shots.

Kept discreteness of X’s


Adjustments

• Takeaways/Giveaways

– Combined into turnovers (TURN)

• Remove non-action events leaving

– GOAL, SHOT, MISS, BLOCK, HIT, FACE, PENL, TURN

• Two full seasons ~510000 events


Valuation of Events

Hockey Low Scoring

Value each event

Short term fluctuation in scoring rates

Net Probability=

P(Goal by Home) – P(Goal by Away) in k seconds

Evaluate k = 5, 6, 7, …, 60

Stability ~ k=10, use k=20 (NP20)


NP20

No change to NP20

HIT, FACE, TURN, BLOCK, MISS

PENL = length in minutes *league average scoring rate/min on PP

SHOT & GOAL = P(SHOT(x,y)=GOAL)+NP20(SHOT)


NP20

SHOT & GOAL = P(SHOT(x,y)=GOAL)+NP20(SHOT)

Offensive Zone 6(X) x 9(Y) grid

Zone behind net

Neutral Zone

Defensive Zone


http://en.wikipedia.org/wiki/Ice_hockey_rink

NP20 Examples: Events by Home


Event Shot Type (if relevant)

Location NP20

SHOT Backhand Off 0.1348 SHOT Wrist Off 0.1096 SHOT Slap Off 0.0697 TURN (to Home Team) Off 0.0362

FAC Off 0.0167 MISS Wrist Off 0.0159 HIT (by Home) Off 0.0039 FAC Neu 0.0026 HIT (by Home) Neu -0.0008 TURN (to Home Team Neu 0.0264

FAC Def 0.0005 HIT (by Home) Def -0.0060

Model

Ridge Regression

𝑁𝑃20 = 𝜇 + 1𝑖𝑗𝐻𝜃𝑗

𝑃𝑗=1 − 1𝑖𝑗

𝐴𝜃𝑗𝑃𝑗=1 + 𝛾𝑍𝑆,

where

m is the impact of home ice advantage on each play,

qj is the effect of player j,

g is the effect of a zone start on the NP20 of each event.

Goalies included for team effects


Results

THoR =Estimated qj’s are per play

Multiply by 67 plays/game (~1/3 of EV)

Multiply by 82 games

Divide by 6 goal differential/win

Wins more than Average

If an equal number of plays


Results

Zone Starts (ZS) Equivalent to replace average player with top 5 forward

Start all shifts in Off Zone = 0.53 goals per game

10 Additional ZS per game = 5.4 goals per season

Home Ice 0.32 goals per game


THoR Top 15 Forwards (2010-2011 & 2011-2012)

Team Player Position Wins

Created St. Louis Blues Alexander Steen C 6.72 Detroit Red Wings Pavel Datsyuk C 6.32 Pittsburgh Penguins Tyler Kennedy C 6.05 Boston Bruins Patrice Bergeron C 5.95 Nashville Predators Patric Hornqvist R 5.88 Phoenix Coyotes Ray Whitney* L 5.62 Pittsburgh Penguins Evgeni Malkin C 5.57 Vancouver Canucks Ryan Kesler C 5.53 Chicago Blackhawks Jonathan Toews C 5.50 Vancouver Canucks Daniel Sedin L 5.47 San Jose Sharks Joe Pavelski C 5.42 Toronto Maple Leafs Mikhail Grabovski C 5.13 Carolina Hurricanes Jeff Skinner C 5.07 Los Angeles Kings Anze Kopitar C 4.93 Pittsburgh Penguins Sidney Crosby* C 4.92


THoR Top 15 Defensemen (2010-2011 & 2011-2012)

Team Player Position Wins

Created Philadelphia Flyers Kimmo Timonen D 5.73 Los Angeles Kings Drew Doughty D 4.07 Edmonton Oilers Tom Gilbert* D 3.32 Columbus Blue Jackets Fedor Tyutin D 3.13 Calgary Flames Mark Giordano D 3.08 Philadelphia Flyers Andrej Meszaros D 2.82 Chicago Blackhawks Brent Seabrook D 2.63 New York Rangers Ryan McDonagh D 2.50 Detroit Red Wings Niklas Kronwall D 2.48 Anaheim Ducks Lubomir Visnovsky* D 2.48 Pittsburgh Penguins Paul Martin D 2.27 Winnipeg Jets Tobias Enstrom D 2.23 Ottawa Senators Erik Karlsson D 2.22 Boston Bruins Zdeno Chara D 2.18 New York Rangers Michael Sauer D 1.95


Reliability


2010 - 20112009 - 20102008 - 2009

100

80

60

40

20

0

Pe

rce

nt

Goals

Penalties

Missed Shots

Blocked Shots

Turnovers

Hits

Shots

Faceoffs

Event

Percentage of Event by Year

Reliability

Choose ridge parameter for small G, here:

G =

1

𝑁𝑇 𝑛𝑘 𝜃 𝑘1−𝜃 𝑘2

2𝑇𝑘=1

1

𝑁 𝑛𝑗 𝜃 𝑗−𝜃

2𝑃𝑗=1

=0.14

Ridge regression

Shrinkage of estimate to zero

Deal with multicollinearity of linemates


Conclusions

“… Look for players with undervalued talents: faceoffs, defensive play vs tough competition, and particularly penalties drawn….”

-Gabriel Desjardins aka Hawerchuk

In blog post about how to build a team following LAKings winning Stanley Cup

http://www.arcticicehockey.com/2012/6/12/3079834/how-did-the-kings-get-here















Conclusions

• THoR Strengths

– Standardized reliable two-way metric (w/ SE’s)

– Adjusts for QoT, QoC, ZS & Home Ice

– Wins Over Average

– Large Sample Size

– Ridge Regression

• THoR Weakness

– RTSS system is weakness

– Adjusted for some known biases from data

– Score Effects (88% plays within 2 goals)

– Don’t see systematic team advantages (goalies in model)


Next Steps

• THoR will go live bi-weekly sometime in March

– www.statsportsconsulting.com/thor

– 2011-12+2013(to date)

• THoR for PP and PK not included in the paper

– THoR=0.8*THoR(EV) + 0.2*THoR(PP/PK)

• Add Rink effects to the model (in process)


http://www.statsportsconsulting.com/thor



Actual Plays Two Years: Top 15 Players

Team Player Position Plays WOA

1 BOSTON BRUINS PATRICE BERGERON C 9621 5.21

2 VANCOUVER CANUCKS RYAN KESLER C 9946 5.01

3 TORONTO MAPLE LEAFS MIKHAIL GRABOVSKI C 10432 4.87

4 CAROLINA HURRICANES ERIC STAAL C 11768 4.86

5 LOS ANGELES KINGS ANZE KOPITAR C 10647 4.77

6 PHILADELPHIA FLYERS KIMMO TIMONEN D 7944 4.64

7 CHICAGO BLACKHAWKS JONATHAN TOEWS C 9276 4.59

8 SAN JOSE SHARKS JOE PAVELSKI C 9316 4.28

9 DETROIT RED WINGS PAVEL DATSYUK C 7442 4.15

10 COLORADO AVALANCHE PAUL STASTNY C 10115 3.91

11 PITTSBURGH PENGUINS EVGENI MALKIN C 7600 3.85

12 DETROIT RED WINGS HENRIK ZETTERBERG L 9692 3.79

13 PHOENIX COYOTES RAY WHITNEY L 7255 3.71

14 SAN JOSE SHARKS LOGAN COUTURE C 9375 3.65

15 VANCOUVER CANUCKS DANIEL SEDIN L 7311 3.64


Acknowledgements


Ongoing Project:

Dennis Lock

Matt Generous

Ed Harcourt

This material is based upon work supported by the National Science Foundation under Grant No. 0959713.

Thank You

[email protected]

[email protected]

@SchuckersM

@EmpiricalSports


mailto:[email protected]



Current THoR (2011-12 + 2013) Top Forwards (82 games, as if)


1 DAVID CLARKSON NEW JERSEY DEVILS R 5.89

2 PATRIC HORNQVIST NASHVILLE PREDATORS R 5.48

3 ERIC STAAL CAROLINA HURRICANES C 5.23 4 MATT DUCHENE COLORADO AVALANCHE C 5.18 5 RAY WHITNEY DALLAS STARS L 5.11

6 TYLER KENNEDY PITTSBURGH PENGUINS C 5.11

7 PATRICK SHARP CHICAGO BLACKHAWKS R 5.09

8 ANZE KOPITAR LOS ANGELES KINGS C 5.06 9 LOGAN COUTURE SAN JOSE SHARKS C 4.94

10 JONATHAN TOEWS CHICAGO BLACKHAWKS C 4.87 11 ZACH PARISE MINNESOTA WILD L 4.87

12 TAYLOR HALL EDMONTON OILERS L 4.85 13 PATRICE BERGERON BOSTON BRUINS C 4.82

14 TEDDY PURCELL TAMPA BAY LIGHTNING R 4.49 15 JOE PAVELSKI SAN JOSE SHARKS C 4.41

Current THoR (2011-12 + 2013) Top Defensemen(82 games)


1 ERIK KARLSSON OTTAWA SENATORS D 4.22

2 BRENT SEABROOK CHICAGO BLACKHAWKS D 3.28

3 DAN HAMHUIS VANCOUVER CANUCKS D 3.13

4 SHEA WEBER NASHVILLE PREDATORS D 2.97

5 KIMMO TIMONEN PHILADELPHIA FLYERS D 2.55

6 NIKITA NIKITIN COLUMBUS BLUE JACKETS D 2.41

7 JASON GARRISON* VANCOUVER CANUCKS D 2.29

8 KRIS LETANG PITTSBURGH PENGUINS D 2.26

9 DMITRY KULIKOV FLORIDA PANTHERS D 2.24 10 ZDENO CHARA BOSTON BRUINS D 2.24 11 MARK GIORDANO CALGARY FLAMES D 2.05

12 NICKLAS LIDSTROM DETROIT RED WINGS D 2.03

13 SLAVA VOYNOV LOS ANGELES KINGS D 1.95

14 DREW DOUGHTY LOS ANGELES KINGS D 1.93

15 FEDOR TYUTIN COLUMBUS BLUE JACKETS D 1.86

Documents

Total Hockey Rating (THoR) - MIT Sloan Sports Analytics Conference