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How it works
Every fighter is rated 0–99 on the four phases of an MMA fight(striking, wrestling, grappling, and cardio + fight IQ) blended into one overall. The scores are derived, not hand-set: each fighter's public UFCStats career numbers are ranked against the rest of the roster and mapped onto the scale. It's a scout-style read to visualize and compare skill sets, not an official rating.
The inputs: UFCStats career averages
For all 176 ranked fighters we start from the eight career averages UFCStats publishes on every fighter's page, plus their win/finish split (KO-TKO / submission / decision) and record:
- Striking: strikes landed & absorbed per minute, accuracy, defense.
- Grappling: takedowns per 15 min, takedown accuracy & defense, submission attempts per 15 min.
- Outcomes: wins, losses, and how the wins came (KO / submission / decision).
These are counting stats: descriptive, opponent-blind, and shaped by style (a counter-striker posts low volume; a control grappler looks quiet on strikes). That's why we read all four axes, not just the composite.
Career numbers → four 0–99 axes
For each component we rank a fighter against the whole roster (a percentile) then blend the components into one axis and map it onto the 60–99 band you see (so the color ramp and bars spread across a visible range). Percentiles, not raw numbers, so a fighter is judged against the field:
The four axes → one Overall
The axes combine into an overall with a striking-heavy weighting. These weights aren't arbitrary: they're backtested against real fight outcomes (a time-aware, leak-free logistic model), tuned so the composite leans on the phases that actually predict who wins. Striking and durability carry the most signal:
A fixed pound-for-pound rank then orders everyone by overall, independent of how the table is sorted or filtered.
Opponent-adjusted (level of competition)
Counting stats are opponent-blind: five takedowns on a debutant look like five on a champion. So we also fit an opponent-adjusted model (FVOA-style) on fight-by-fight data: each phase is credited against the fighters actually faced, with partial pooling and small-sample shrinkage. That yields each fighter's strength of schedule and adjusted striking / wrestling / takedown-defense, shown on profiles once the model has run.
Win probability (Compare)
On the compare page a matchup model turns two fighters' stats into a win probability: takedowns vs. takedown defense, KO threat vs. durability, striking differential, and more. It's a logistic model trained on real fight results with time-aware (leak-free) features, so the reported accuracy is honest, currently ~68% on held-out fights. Not betting advice.
What this is, and isn't
This is a scout-style read from public career numbers: a useful lens, not a perfect rating. Counting stats are descriptive and style can beat stats, so the composite is opinionated by design. Read the four axes together, lean on the opponent-adjusted view for context, and treat the win probability as a model's best guess, not a lock.