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Clark Hayashi
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Analysis complete · recommendations proposed

Who comes back to play again?

Intramural Sports Participation Analysis

Eight seasons of participation records, turned into a clearer picture of who signs up, who plays, and who comes back.

Was the program losing players, or were the numbers telling us something else?

Actual participation held roughly steady from 2022 through 2024, then fell in 2025. Declining new-player intake pointed toward an acquisition problem.

My role

I was the sole analyst: I consolidated and cleaned the records in Excel, built Tableau dashboards, and developed recommendations. Nearly four years inside the program, as an official and later a manager, helped me know which questions to ask.

2018-2025 · 8 seasons · 4,169 player-years · Excel and Tableau

What the records showed

Actual players held steady before the 2025 decline

Players with at least one game · scale 0-800

Players who appeared in at least one game, 2022-2025. Source: aggregate findings from my intramural participation analysis.
View chart data
Actual players held steady before the 2025 decline
YearPlayers with at least one game
2022711
2023721
2024720
2025648
What this suggests

Track interest and attendance separately. The share of rostered players who showed up rose from 47% to 64% over 2022-2025.

Players who played more were more likely to return

Returned the following year · scale 0-100%

Next-year return rates across 2,430 new players, grouped by games played in their first year. Source: aggregate findings from my intramural participation analysis.
View chart data
Players who played more were more likely to return
Games played in first yearReturned the following year
1-2 games23%
3-5 games49%
6-10 games66%
11+ games84%
What this suggests

Test ways to help new players finish a league and find the next one. This association does not prove that extra games cause retention.

Three more findings

The front door was narrowing

New-player intake fell from 371 to 339 to 323 to 283 over four years, a 24% decline. Returning players covered the gap until 2025. That points attention toward how people first find and join the program.

People came back together

Players whose social group persisted returned at 70-78%, compared with 29% when the group dissolved. Only 42% of groups persisted. Group continuity and individual return are linked decisions, so this does not isolate a causal effect.

A small core carried a lot of activity

The top 10% of players, 293 people, generated 44.5% of recorded activity. Captains returned at 55%, compared with 43% for other players. Captains are a useful contact point, and reliance on a small core is also a risk.

What I recommended

Proposals based on the analysis. These are not reported as changes the university has adopted.

  1. Separate interest from attendance

    Report rostered students and students who played as two named measures. Every target should say which it means.

  2. Give recruitment an owner

    Set a new-player intake target and ask how students heard about the program at registration.

  3. Help players reach their next league

    Protect new-player leagues from forfeits and make the next opportunity easy to find, within the same sport or across sports.

  4. Make it easier for teams to return

    Simplify team renewal, prompt graduating captains to name a successor, and test captain-led recruitment.

Why this mattered to me

I knew this program as a player, employee, and manager. As my data skills grew, I wanted to put them to use for a community I cared about, so I took the initiative to investigate the participation records and look for ways to help.

My intramural team in red jerseys with a championship belt Our group on a ball field with a championship belt A team in Seattle University jerseys holding an intramural championship belt on the field A basketball team in red jerseys with a championship belt in the Seattle University gym

Method and limits

These findings describe associations, not causal effects. The analysis and dashboards are complete. UREC brought back the t-shirt prize promotion from these recommendations; the others remain proposals. Student-level records belong to the university; only aggregate findings are shown here.

Read the analysis method

I consolidated and cleaned 2018-2025 participation records in Excel and analyzed cohorts by first-played year. For group continuity, I matched next-year teams in the same sport family sharing at least three members or a Jaccard overlap of 0.4 or more. Team names alone were too noisy: about 10% persisted, compared with 42% of the underlying groups.

What I took from the work

Working inside the program helped me ask practical questions. The analysis then challenged the initial reading of participation: fewer roster spots did not always mean fewer people playing.