Ain’t played nobody: Building an optimal schedule to secure an NCAA tournament berth

Author: 
Date created: 
2019-08-12
Identifier: 
etd20495
Keywords: 
College basketball
March Madness
Scheduling
Sports analytics
Machine learning
Abstract: 

American men’s college basketball teams compete annually for the National Collegiate Athletic Association (NCAA) national championship, determined through a 68-team, single-elimination tournament known as “March Madness”. Tournament participants either qualify automatically, through their conferences’ year-end tournaments, or are chosen by a selection committee based on various measures of regular season success. When selecting teams, the committee reportedly values a team's quality of, and performance against, opponents outside of their conference. Since teams have some freedom in selecting nonconference games, we seek to develop an approach to optimizing this choice. Using historical data, we find the committee's most valued criteria for selecting tournament teams. Additionally, we use prior seasons’ success and projected returning players to forecast every team’s strength for the upcoming season. Using the selection criteria and these projections, we develop a tool to help teams build the optimal nonconference schedule to increase their NCAA tournament selection probability.

Document type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Senior supervisor: 
Thomas Loughin
Department: 
Science: Department of Statistics and Actuarial Science
Thesis type: 
(Project) M.Sc.
Statistics: