Evaluating Olympic Sports
Two-stage AHP + TOPSIS decision model for which sports should enter future Olympics. HiMCM 2024 Problem A · Meritorious Award (Top 13%).
- Contest: HiMCM 2024, Problem A
- Team: 15621
- Result: Meritorious Award (top 13%)
The question
If the International Olympic Committee had to decide which sports, disciplines, or events (SDEs) to add to a future Olympic Games using a reproducible evaluation framework rather than a one-off political decision, what should that framework look like?
Our approach
We built a two-stage model.
- Stage 1 — Analytic Hierarchy Process (AHP). We identified six IOC criteria (popularity and accessibility, gender equity, sustainability, infrastructure demand, athlete welfare, youth appeal) and ten underlying factors, then used pairwise comparisons to produce a logical weighting across them.
- Stage 2 — TOPSIS. We scored each candidate sport by how closely it matched an “ideal” sport profile, weighted by the AHP output. TOPSIS gave us a clean, interpretable ranking rather than a black-box score.
Performance
On historical IOC decisions, our ranking recovered them with 73.91% accuracy, 83.02% precision, 83.02% recall — strong enough to argue the framework is capturing real IOC preferences rather than noise.
Takeaways
Modeling contests teach you that “building a model” is less about picking fancy methods and more about picking methods whose assumptions you can defend to a reader. AHP + TOPSIS is a cliché combination for a reason: the weights are explicit, the ranking is explicit, and you can argue with every step of it.