NFL Prediction using Committees of Artificial Neural Networks
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John A. David
, R. Drew Pasteur , M. Saif Ahmad and Michael C. Janning
This paper analyzes the ability of a neural network model to predict the outcome of NFL games. This model uses only readily available statistics, such as passing yards, rushing yards, fumbles lost, and scoring. A key component of this model is the use of statistical differentials to compare teams. For example, the offensive passing yards gained by one team are compared to the defensive passing yards allowed by an opposing team to create a data set of expected values for a given matchup. By using principal component analysis and derivative based analysis, we determined which statistics influence our model the most. We assessed the performance of the model by comparing its performance to that of published prediction algorithms and the Las Vegas oddsmakers over multiple seasons. Two novel aspects of this work include the use of multiple committees of machines for prediction and the use of our model to simulate virtual round-robin tournaments to establish an objective ranking of the teams.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Articles in the same Issue
- Conference Paper
- Uncovering Europe's Best Goalscorers from the 2009-2010 Season
- Dynamic Effort, Sustainability, Myopia, and 110% Effort
- The Intra-Match Home Advantage in Australian Rules Football
- The Relationship between Leader Experience and Team Performance in Cross-Sectional and Longitudinal Designs
- Stratified Odds Ratios for Evaluating NBA Players Based on their Plus/Minus Statistics
- Dependence Relationships between On Field Performance, Wins, and Payroll in Major League Baseball
- Optimal Dynamic Clustering Through Relegation and Promotion: How to Design a Competitive Sports League
- Perception ? Reality: Analyzing Specific Allegations of NBA Referee Bias
- NFL Prediction using Committees of Artificial Neural Networks
- An Alternative to the NFL Draft Pick Value Chart Based upon Player Performance
- Monte Carlo Simulation for High School Football Playoff Seed Projection
- Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters
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- Never Too Late to Win
- An Extension of the Pythagorean Expectation for Association Football
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- Valuing Nostalgia: The Case of the Topps 1957 Baseball Cards