The Determinants of Scoring in NFL Games and Beating the Over/Under Line
C. Barry Pfitzner et al.
What the paper says
In this paper we attempt to predict the total points scored in National Football League (NFL) games for the 2005-2006 season. Separate regression equations are identified for predicting points for the home and away teams in individual games based on information known prior to the games. The predictions from the regression equations (updated weekly) are then compared to the over/under line on individual NFL games in a wagering experiment to determine if a successful betting strategy can be identified. All predictions in this paper are out-of-sample. Using this methodology, we find that several successful wagering procedures could have been applied to the 2005-2006 NFL season. We also estimate a single equation to predict the over/under line for individual games. That is, we test to see if the variables we have collected and formulated are important in predicting the line for NFL games.
3 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.00 × 0.4 = 0.00 |
| M · momentum | 0.20 × 0.15 = 0.03 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.