These lessons are created for students grade 4-ish and above in partnership with Stanford Women’s Basketball. One of the goals of these lessons is to show students that data is everywhere – you don’t have to be an athlete to be involved in sports. Sports Data Analytics is a huge field. Teams have statisticians and coaches that analyze data to support recruiting, practice decisions, and strategies for players and ways to be ready for opposing teams. Even the players need to understand their and their opponents data. In this unit of lessons, students ask questions, explore, visualize and make decisions with data inside basketball. 

Note: Any teacher can teach these lessons – you DO NOT have to know basketball. All the information needed is in the videos made by Stanford basketball players. Students will happily lead the discussions, and explain the rules to each other as needed. 

There are three parts to this sports data analytics unit of work:

• In Part 1 students are introduced to basketball data through video made for them by Stanford women’s basketball team, through a data recording activity and through playing a version of the game at their tables. 
• In Part 2 students are introduced to CODAP, a cool data visualization tool, to consider the height of players using dot plots, histograms and mean, median and mode. 
• In Part 3 students conduct a data investigation with the goal of choosing their dream team! Students pick a five player team from all ACC & PAC-12 players from last year, justifying their choices using statistics and graphs. They will work in CODAP to choose, analyze and communicate data, and then defend their choice of players. 

*Note: Mary Ashley Stevenson and Tess Heal have been added to this data set since they played for different teams last year but play for Stanford this year.

In partnership with Stanford Women’s Basketball, CBB Analytics, and the Sports Analytics Club Program.

View a video of a 6th grade class using this unit here.