MIDAS organizes a series of student meetings with industry representatives. Students learn about data science in the industry and career preparation. To receive email notifications for such events, please contact our Education Program Manager, Trisha Fountain.
The Michigan Institute for Data Science (MIDAS) and the Exercise & Sport Science Initiative (ESSI) are excited to announce the 2020 Basketball Data Madness Challenge for students with an interest in data science. Student teams of up to 4 members will be given access to two datasets on Michigan Basketball player performance loads and overall game statistics. Teams will have one week to analyze the datasets (on your personal computers) and answer predefined questions from the challenge organizers. Final questions will be similar to the following examples:
1) How do performance loads relate to game outcomes (e.g., win/loss)?
2) How do player performance loads relate to game dynamics (e.g., turnover)?
In the spirit of March Madness, 4 winning teams will be selected by a panel of U-M data scientists and will each receive a $400 “Final Four” prize. The judging will be based on both the scientific content and the communication of results. We look for well-designed and well-communicated projects at any level of expertise.
Both graduate and undergraduate students, at all levels of data science expertise, are welcome to participate. One team member should register the entire team by Friday, March 13. You may also register as an individual and MIDAS will help you form teams. Only 16 teams will be accepted to compete.
Challenge Timeline:
March 13 – Team Registration Closes
March 16 – Data Challenge Kickoff Event – Learn about the challenge datasets.
March 30 – Submissions due electronically via Box. Any copies of the data must be deleted after the 30th.
April 6 – Final Four winners will be announced. Cash prizes will be awarded.
Judges
| Name | Title | Affiliation |
| Alex Wong | Associate Athletic Trainer | Michigan Basketball |
| Blair Winograd | Research Fellow | MIDAS |
| Qianying Lin | Research Fellow | MIDAS |
| Stefan Szymanski | Stephen J. Galetti Collegiate Professor of Sport Management | Kinesiology |
| Tom Finholt | Dean and Professor of Information | School of Information |
| Maria Veiga | Research Fellow | MIDAS |
Questions about the data challenge? E-mail MIDAS Education Program Manager, Trisha Fountain (tvfount@umich.edu).
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