MMA Desk — Model Anchor Calibration Prompt

Context: Our MLB Player Props council (2026-04-03) established the universal framework: per-possession/per-PA rates as foundation, Bayesian shrinkage toward career prior, Log-Odds opponent adjustment, Gaussian copula for correlated combo props, dual-anchor system (sportsbook + model) tracked via Brier scores, confidence tiers. This prompt asks for the SPORT-SPECIFIC parameters to plug into that framework.

MMA Desk — Model Anchor Calibration

We are building model anchors for MMA/UFC betting markets on Kalshi: fight winner, method of victory, over/under rounds.

Questions:

1. What fighter metrics best predict fight outcomes? (Elo, significant strike differential, takedown defense, reach?)
2. How should style matchups affect projections? (Wrestler vs striker, grappler vs grappler?)
3. How many fights until fighter Elo stabilizes? (Fighters only compete 2-3x per year)
4. How should weight class changes affect fighter ratings?
5. How to model method of victory distribution? (KO/TKO, submission, decision probabilities)
6. How to model total rounds? What distribution for 3-round vs 5-round fights?
7. How should camp changes and training partner quality factor in?
8. How should layoff length (time since last fight) adjust projections?
9. Age curve for MMA fighters? Different from other sports?
10. How should weigh-in data (missed weight, large cuts) factor in?
11. Give specific numbers, formulas, and implementation-ready recommendations.