Betting on NHL Games - PowerPoint PPT Presentation

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Betting on NHL Games

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Playoff Indicator. Visiting Team Indicator. Consensus Expectation = Opening Line. 6/3/09 ... Incorporation of Schedule Strength. 6/3/09. 17. Absolute Model ... – PowerPoint PPT presentation

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Tags: nhl | betting | games | nfl | playoff | schedule

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Title: Betting on NHL Games


1
Betting on NHL Games
  • Matthew S. Baker
  • Principal
  • Edge Research

2
Why Hockey?
  • If you want to find bets based on doing your own
    analysis of existing data, I suggest staying away
    from the National Football League.
  • Stanford Wong
  • NHL the smallcap of sports betting

3
Game of Hockey
  • Similar to soccer
  • 3 periods of 20 minutes, most goals wins
  • Each team has 3 offense, 2 defense, 1 goalie
  • Substitutes on the fly
  • 82 game regular season
  • Baseball style series post season

4
Legal Betting
  • Las Vegas
  • good odds, safe, inconvenient
  • Internet
  • good odds, less safe, convenient
  • Offshore
  • less good odds, safe, inconvenient

5
Betting Fundamentals
  • Money Line
  • Negative is favorite -150 means betting 150
    wins 250 if you are right, else lose 150.
  • Positive is underdog 150 means betting 100
    wins 250 if you are right, else lose 100.

6
The Data
  • All NHL games 1997 - 2002
  • Home team, visiting team
  • Final score
  • Regular season or playoff game
  • Opening money line

7
Visitor Team Scoring
8
Home Team Scoring
9
Visitor Team Payoffs
10
Home Team Payoffs
11
Regular Season
  • Average Visitor Score 2.57
  • Average Home Score 2.82
  • Visitor Win Rate 38
  • Home Win Rate 48
  • Tie 14
  • Average Line 139

12
Playoffs
  • Average Visitor Score 2.35
  • Average Home Score 2.60
  • Visitor Win Rate 47
  • Home Win Rate 53
  • Tie 0
  • Average Line 149

13
Model Variables
  • Trailing 20 Game Win Rate
  • Trailing 50 Game Win Rate
  • Trailing 20 Game Goals For / Against
  • Trailing 50 Game Goals For / Against
  • Playoff Indicator
  • Visiting Team Indicator
  • Consensus Expectation Opening Line

14
Solution Framework
  • Chance Team A Beats Team B
  • NORMSDIST( (MuA MuB) / SQRT(SigA2 SigB2) )
  • MuA, MuB, SigA, SigB not observable
  • Use historical data to estimate

15
Univariate Visitor Win Rate
16
Stages of Model Development
  • Multivariate/Backward on Absolute Win Chance
  • Multivariate/Backward/Ridge on Relative Win Chance
  • Incorporation of Schedule Strength

17
Absolute Model Results
18
Relative Model Results w/SS
19
Simulation Results
20
Further Research
  • Shots on net
  • Goalie save percentage
  • Out of sample (2002/2003 season)
  • Live testing!

21
Conclusions
  • Bet on visitors during playoffs
  • Bet on underdogs
  • Bet on team with worse recent record, but
    comparable or better goal scoring

22
References
  • Wong, Stanford, Sharp Sports Betting
  • Thorp, Ed, The Kelly Criterion in Blackjack,
    Sports Betting, and the Stock Market
  • McCune, Bob, Insights into Sports Betting
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