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Relevancy:63%
Fair Decathlon Model. Part 6: Day Two. Technical Gates, Throwing Delegations, and the Event That Refuses to Behave.
Rafał Snoch examines the five Day Two events through 100-point FDM-40N cohorts, revealing how technical failures, specialist strengths, exceptional performances and contrasting athlete populations shape the residuals behind the scoring model.
Relevancy:50%
Fair Decathlon Model. Part 6: Day One. Visitors, Ceilings, and the People Behind the Residuals.
Rafał Snoch examines the five Day One events through 100-point FDM-40N cohorts, revealing how individual specialists, weak-event survivors and population patterns shape the residuals behind the scoring model.
Relevancy:13%
Fair Decathlon Model. Part 3: Forty Seasons, Cleaner Data, and Wider Calibration
How a larger and stricter sample changed the formulas without changing the conclusions
Relevancy:13%
Fair Decathlon Model. Part 4: Does FDM Balance the Ten Events?
A leave-one-event-out test of 17,277 complete decathlon performances
Relevancy:13%
Fair Decathlon Model. Part 5: How Far Down Does FDM Continue to Balance the Ten Events?
A leave-one-event-out test from 7,000 to 4,000 points
Relevancy:13%
Fair Decathlon Model. Part 7: Can Decathlon Calibrate Itself?
This article asks whether the decathlon’s own performance data can provide enough information to calibrate a fair scoring system without relying primarily on elite athletes. Using 27, 741 complete decathlons—and a separate dataset excluding all …
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