Basketball Motion Analysis using Decomposition
In the Basketball Motion Analysis lesson, students use decomposition to break down a specific LeBron James play from the 2015 NBA Finals. Students practice drawing and interpreting speed graphs, as well as discuss whether computers and data can replace human basketball coaches. This lesson was inspired by a post by Savvas Tjortjoglou.

Topics addressed:
Speed / motion graphs
Basketball strategy

Primary CT concept: decomposition. Students begin by watching television footage of the play, which is full of sounds, camera flashes, changing angles, hundreds of people, etc. We use decomposition to break down the play into something more manageable, removing most of the players and all of the other distractors to focus solely on the ball and the four most relevant players.

Students will be able to:
Define decomposition and give examples of breaking down difficult problems into smaller pieces
Discuss how the NBA collects motion tracking data on players during games, and what that data is used for
Interpret the general shape of speed graphs as they relate to someone moving in one dimension
Create a speed graph to represent their observation of someone walking at varying speeds
Debate the balance of computers and algorithms vs direct human observation and traditional coaching in basketball analysis
Read specific values from a speed graph, including speed at specific times, maximum speeds and determining when a given speed is reached

Read about how the NBA tracks its players during games on Wikipedia at

Suggested lesson breakdown:
5-10min – introduction to decomposition, examples outside of this lesson
15-20min – overview of how NBA tracks players and discussion of what that data can be used for
10min – introduction to speed graphs, full-class practice
10min – analysis of the play we’re analyzing
5-10min – interpreting speed graphs and discussing the answers to our questions
20min – individual practice on worksheet

For further information and relevant standards, please visit


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Created: Jan 23, 2017

Updated: Feb 22, 2018


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Creative Commons "Sharealike"