You are not currently logged in.
Access JSTOR through your library or other institution:
Predictions for National Football League Games Via Linear-Model Methodology
Journal of the American Statistical Association
Vol. 75, No. 371 (Sep., 1980), pp. 516-524
Stable URL: http://www.jstor.org/stable/2287640
Page Count: 9
You can always find the topics here!Topics: Games, Betting, Statistical forecasts, Statistical variance, Statistical estimation, Applied statistics, Maximum likelihood estimation, Arithmetic mean, Tie lines, College athletics
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Preview not available
Results on mixed linear models were used to develop a procedure for predicting the outcomes of National Football League games. The predictions are based on the differences in score from past games. The underlying model for each difference in score takes into account the home-field advantage and the difference in the yearly characteristic performance levels of the two teams. Each team's yearly characteristic performance levels are assumed to follow a first-order autoregressive process. The predictions for 1,320 games played between 1971 and 1977 had an average absolute error of 10.68, compared with 10.49 for bookmaker predictions.
Journal of the American Statistical Association © 1980 American Statistical Association