P redicting the outcomes of National Football League games
By B. Boulier, Herman O. Stekler. 2003
132 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Gender Studies, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/368d04b97e1fdffea35203676ed86e8cc508a75a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Achim Zeileis
- Kurt Hornik
- Gerd Gigerenzer
- Daniel G. Goldstein
- David Sendor
- Richard Verlander
- Herman O. Stekler
- Torsten Hothorn
In Gender Studies
In Management Science and Operations Research
- Gerd Gigerenzer
- Daniel G. Goldstein
- David Sendor
- Richard Verlander
- Kurt Hornik
- Achim Zeileis
- Herman O. Stekler
- Robin M. Hogarth
Citations in the corpus
- Issues in Sports Forecasting (2010, methodology): “…market, with a 72% success rate in selecting the winner, was more accurate than his statistical procedure, which was right 70% of the time.22 Boulier and Stekler (2003) used the power scores published in the New York Times and analyzed the forecast: the team with the higher power score…”
- Fast and frugal forecasting (2009, background): “World rankings and expert seeding have been shown to be good predictors of sport outcomes (Boulier & Stekler, 1999, 2003).”
- Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EURO 2008 (2010, background): “Due to the increasing popularity of online sports betting, bookmakers odds are a type of data that is abundant and easily available and that has been successfully employed in forecasts of single matches (e.g., Vlastakis et al., 2009; Spann and Skiera, 2009; Song et al., 2007; Forrest et al., 2005b; ”
- Predicting Wimbledon 2005 tennis results by mere player name recognition (2007, unknown): “…city sizes (Goldstein & Gigerenzer, 2002), predicting stock performance in a bull market (Borges, Goldstein, Ortmann, & Gigerenzer, 1999; but see Boyd, 2001, for a bear market), predicting record sales of pop stars (Herzog, 2005), the quality of American colleges (Hertwig & Todd, 2003), and the…”
- How often does the best team win? A unified approach to understanding randomness in North American sport (2017, background): “This includes contrasting league-level characteristics in economics [Leeds and Von Allmen (2004)], estimating game-level probabilities in statistics [Glickman and Stern (1998)] and classifying future game winners in forecasting [Boulier and Stekler (2003)].”