Journal of Quantitative Analysis in Sports
An official journal of the American Statistical Association
Editor-in-Chief: Mark Glickman PhD
SCImago Journal Rank (SJR) 2014: 0.265
Source Normalized Impact per Paper (SNIP) 2014: 0.513
Impact per Publication (IPP) 2014: 0.452
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Most Downloaded Articles
- Creating space to shoot: quantifying spatial relative field goal efficiency in basketball by Shortridge, Ashton/ Goldsberry, Kirk and Adams, Matthew
- A generative model for predicting outcomes in college basketball by Ruiz, Francisco J. R. and Perez-Cruz, Fernando
- Predicting the draft and career success of tight ends in the National Football League by Mulholland, Jason and Jensen, Shane T.
- Building an NCAA men’s basketball predictive model and quantifying its success by Lopez, Michael J. and Matthews, Gregory J.
- openWAR: An open source system for evaluating overall player performance in major league baseball by Baumer, Benjamin S./ Jensen, Shane T. and Matthews, Gregory J.
Comparing Team Selection and Seeding for the 2011 NCAA Men's Basketball Tournament
1California State University, Chico
2California State University, Chico
Citation Information: Journal of Quantitative Analysis in Sports. Volume 8, Issue 1, ISSN (Online) 1559-0410, DOI: 10.1515/1559-0410.1369, March 2012
- Published Online:
The men’s NCAA basketball tournament is a popular sporting event often referred to as “March Madness.” Each year the NCAA committee not only selects but also seeds the tournament teams. Invariably there is much discussion about which teams were included and excluded as well as discussion about the seeding of the teams. In this paper, we propose an innovative heuristic measure of team success, and we investigate how well the NCAA committee seeding compares to the computer-based placements by Sagarin and the rating percentage index (RPI). For the 2011 tournament, the NCAA committee selection process performed better than those based solely on the computer methods in determining tournament success.