Introduced by Vikram Singh, Dong-Eun Suh, Karl Walter, Dian Yu and Francis Yang
NBA Make-A-Team, a new project developed by UC Berkeley students, gives NBA coaches, general managers and everyday fans the opportunity to select hypothetical starting lineups and get accurate feedback on how that basketball team would perform.
This simple-to-use tool can project a team’s winning percentage and predict its statistical strengths and weaknesses. It can also suggest a player swap that could help a user build a stronger team.
The tool empowers the user to assemble their dream team – choosing from players that were part of the NBA between 2000 to 2017 – and compare that team against their friends’ squads-of-choice. Additionally, for those who hope to make their dream team a realistic team, there is a salary cap option that imposes a league’s spending limits on chosen players.
This project was developed by a team of students from Data-X, a project-oriented data and machine learning course at UC Berkeley. The largest hurdles the team faced were cleaning and processing the data and developing the models used to estimate a team’s winning percentage and to suggest player swaps.
This project is tremendously exciting because it provides instantaneous feedback on both real and hypothetical rosters and gamifies roster selection by highlighting team weaknesses and strengths.
See how it works here.