Year: 2007
Type: article
Abstract: Scores in professional American football games follow a distribution that is noticeably skewed towards larger values. However, the difference between the home teams’ scores and the road teams’ scores (the point spreads) do follow a distribution that is very close to Normal. Furthermore, the residuals from linear regressions of the point spreads on the Las Vegas betting spreads and on partial game point spreads (e.g., the point spreads at half-time) are also very close to Normal, and suggest that a linear model is appropriate. These data are also suitable for logistic regression problems, such as estimating the probability that the home team wins given the betting spread, the half time score, or both. This presents an ideal setting for teaching simple and multiple linear regression and logistic regression procedures for any level of statistics course.
Author: Philip J. Everson
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2556748531