football: Football Point Spreads and Game Outcomes

In BayesDA: Functions and Datasets for the book "Bayesian Data Analysis"

Description

Data on football point spreads and game outcomes (north american football) for ten seasons, 1981, 1983-1986, 1988-1992, each season are 224 games and they are strung together. Only three first seasons are used in chapter one of book.

Usage

data(football)

Format

A data frame with 2240 observations on the following 7 variables.

home

home indicator

favorite

favorite score

underdog

underdog score

spread

point spread

favorite.name

a factor with levels ATL BUF CHI CIN CLE DAL DEN DET GB HOU IND KC LAA LAN MIA MIN NE NO NYG NYJ PHA PHX PIT SD SEA SF TB WAS

underdog.name

a factor with levels ATL BUF CHI CIN CLE DAL DEN DET GB HOU IND KC LAA LAN MIA MIN NE NO NYG NYJ PHA PHX PIT SD SEA SF TB WAS

week

a numeric vector

Details

Football experts provide the point spread as a measure of the difference in ability between the two teams. For example, team A might be a 3.5 favourite to team B. The implication of this is that the proposition that team A, the favourite, defeats team B, the underdog, by 4 or more points, are considered a fair bet. In other words, the probability that A wins by more than 3.5 points is 0.5. If the point spread are an integer, then the implication is that team A is as likely to win by more points than the point spread as it is to win by fewer points than the point spread (or to loose). If the win is by exactly the point spread then neither side is paid off.

Examples

data(football)
summary(football)
names(football)
# In chapter 1 only three first seasons are used:
cap1 <- football[1:672, ]

BayesDA documentation built on May 1, 2019, 6:33 p.m.