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Sports Analytics Department

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Grades 9-1290 minSource: Creative Dad Company

Students turn a stack of real sports performance data—shooting percentages, sprint times, whatever the team can gather—into a specific, testable recommendation a coach could actually use. It's a perfect project for a stats-curious sports fan.

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Every level teaches the same core idea — pick the one that fits your time, budget, and energy today.

Prep: 10 minActivity: 30 min1 session~$2/groupOne table for the Sports Analytics Department evidence and prototypeBeginner-friendly

Setup

Print or handwrite the four Sports Analytics Department challenge steps and place common paper supplies on one table. Prepare one small sample, dataset, scenario, or recycled-material model drawn directly from the project description; no device, paid tool, room decoration, or purchased kit is required.

Activity

  1. Read the Sports Analytics Department challenge aloud, then pick a sport and a specific stat—like free-throw percentage under fatigue—and predict what pattern the data will show.
  2. Use paper, index cards, recycled objects, or facilitator-provided sample data to collect or use provided performance data and build a simple chart or model showing the pattern.
  3. Run one tabletop trial and find an outlier or inconsistency in the data that complicates the obvious conclusion, and dig into why it happened.
  4. Finish by present one specific, testable recommendation to a coach, and explain what data would prove the recommendation right or wrong; record the evidence that supports the decision.

Done when: The group completes a defensible Sports Analytics Department solution, records at least one test result or comparison, changes one claim or design in response, and supports its final decision with that evidence.

Materials

stopwatch, measuring tape, graph paper, calculator, poster board

Shown for the Quick Start version — switch tabs above to see what changes.

Disclosure: Materials links below go to Amazon. As an Amazon Associate, Creative Dad Company earns from qualifying purchases at no extra cost to you.

Steps

  1. Pick a sport and a specific stat—like free-throw percentage under fatigue—and predict what pattern the data will show.
  2. Collect or use provided performance data and build a simple chart or model showing the pattern.
  3. Find an outlier or inconsistency in the data that complicates the obvious conclusion, and dig into why it happened.
  4. Present one specific, testable recommendation to a coach, and explain what data would prove the recommendation right or wrong.