Sports scheduling has been transformed over the last fifteen year. Prior to then, most sports leagues used hand-crafted schedules that met few of the needs of the leagues. Better computational techniques from fields such as integer programming and constraint programming, along with vastly improved computational resources, mean that most current schedules are automatically generated and are able to meet many more of the needs of the teams and leagues. Drawing on my 15 years of scheduling Major League Baseball and more than two decades of scheduling college sports, I will outline some of the key advances and explore how analytics can be used to allow leagues to move beyond “most playable schedule” to “most profitable schedule”.
Michael Trick is the Dean of Carnegie Mellon University in Qatar and the Harry B. and James H. Higgins Professor of Operations Research at the Tepper School of Business, Carnegie Mellon. Dr. Trick received his doctorate in Industrial Engineering from the Georgia Institute of Technology, and has been a faculty member at CMU since 1989. Dr. Trick’s research interests include computational social choice, combinatorial and network optimization, constraint programming, and the application of operations research techniques to real-world problems. Trick is the author of more than 50 journal publication and five books. He has consulted extensively on the use of optimization to solve difficult, practical problems. His clients have included the Internal Revenue Service, the Federal Communications Commission, Motorola, and many sports leagues, including college conferences such as the ACC and SEC, and Major
League Baseball. He was part of the INFORMS Edelman-Prize winning team for his work on reallocating communications spectrum for the FCC. He is a past President of INFORMS (The Institute for Operations Research and the Management Sciences) and is the Immediate Past President of IFORS (the International Federation of Operational Research Societies). He is a fellow of both of those societies.