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Analyzing NHL Goalie Stats (03-04 07-08) Using the Self-Organizing - - PowerPoint PPT Presentation

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Analyzing NHL Goalie Stats (03-04 07-08) Using the Self-Organizing Map By: Chuck Crittenden "In hockey, goaltending is 75 percent of the game. Unless it's bad goaltending. Then it's 100 percent of the game, because you're going to

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Analyzing NHL Goalie Stats (03-04—07-08) Using the Self-Organizing Map

By: Chuck Crittenden

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"In hockey, goaltending is 75 percent of the game. Unless it's bad goaltending. Then it's 100 percent of the game, because you're going to lose." ~ Gene Ubriaco (NHL forward)

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Overview

l Previous Problem l Data l Algorithm l Self-Organizing Map

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Overview

l Specific Maps l Alternate Paths l Conclusion l Extensions

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Previous Problem

l NHL Goaltending Statistics by Team – (03-04 through 07-08) l Average Standings for each Team l Use Self-Organizing Map – Find natural clusters

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Previous Problem

l Stats – GAA, SV %,

GA, GF, DIFF

l Standings and Levels

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The Result

l 15x15 Map

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The Data

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Data

l GAA – Goals Against Average

Goals Allowed ` Number of Minutes Played(1/60)

l SV% – Save Percentage

Goals Allowed Shots Allowed

l GA – Goals Allowed l GF – Goals Scored l DIFF – Goal Differential

DIFF = Goals Scored – Goals Allowed

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The Algorithm

l Self-Organizing Map (SOM) – Artifical Neural Network l Clusters in 2-dimensional map

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What is Needed?

l A .bat file containing the reference to the

executables and the specifics of the map.

l The executables randomly initialize, run the

algorithm, and calibrate the label onto the points.

l som_mapper.exe

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Initial Map

l Randomly intialized. l Each team (p) compared to each point on

the map (q) with Euclidean distance.

l Whichever point the specific team is closest

to.

l That point is trained accordingly. l Other points around it are also trained,

just not as much.

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SOM

l Process repeats for a set number of times. l The labels are pasted on to each instance. l The Map is made.

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Team-Specific Maps

l Using only randinit and vsom l Use a specific team’s data only – Use vcal to attach the labels of each season l Allows monitoring of team’s progress

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Boston Bruins

Point Totals 03-04 104 05-06 74 06-07 76 07-08 94

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Boston’s Map

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Year-Specific Maps

l Using only randinit and vsom l Use a specific season’s data only – Use vcal to attach the labels of each team l Allows monitoring of every team’s

performance when maps put consecutively

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2003-2004 Map

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2005-2006 Map

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Alternate Means

l Rather than use same map as base l Use a seed for the randomization process – In theory will force better teams into the same

section for all maps

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Randomization

l Didn’t work out as planned.

03-04 05-06

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Conclusion

l In SOM using a map with all of the data is

superior to a seed

– Assuming data is representative l Is possible to monitor team’s progression

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Extensions

l This same idea can be used to track a single

goalie

– Removing GA, GF, and DIFF – Using only their data matched against all of the

data in the league

l Compare two or more teams in separate

years

l Use more attributes to compare individual

players

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Summary

l Previous Problem l Data l Algorithm l Self-Organizing Map

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Summary

l Specific Maps l Alternate Paths l Conclusion l Extension

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Sources

Aleshunas, John. Retrieved Apr. 17, 2008. “Self-Organizing Map (SOM)” from: http://mercury.webster.edu/aleshunas/MATH%203210/MATH%203210%20Source%20Code%20and%20Executables.html Aleshunas, John. Retrieved Dec. 9, 2008. “Crittenden – NHL Goalie SOM” from: http://mercury.webster.edu/aleshunas/Support%20Materials/SOM/Crittenden%20-%20NHL%20Goalie%20SOM.doc Goaltender’s Annex. Retrieved May 5, 2008. Ubriaco Quote from: http://www.angelfire.com/sk/goalieannex/quotes02.html NHL.com. Retrieved Apr. 16, 2008. “Goalie Statistics and Team Standings” from: http://www.nhl.com/nhlstats/app Yahoo Sports. Retrieved Apr. 16, 2008. “Goalie Statistics and Team Standings” from: http://sports.yahoo.com/nhl/teams/___/stats (Replace ___ with each team’s abbreviation).

  • Wikipedia. Retrieved Apr. 17 2008. “Stepping through the Algorithm” from:

http://en.wikipedia.org/wiki/Self-organizing_map - Stepping_through_the_algorithm

  • Wikipedia. Retrieved May 6, 2008. “Euclidean Distance” from:

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