Find the right fighter.
Know who to call.
Turn a matchmaking or recruiting need into an evidence-backed shortlist. Filter fighters by division, age, performance, geography, activity and verified opportunity status, then inspect management, contract evidence and public contact paths.
From opening to shortlist.
Start with the fighter you need, narrow the candidate pool, inspect the evidence, then find the best verified route to the fighter or their representation.
Find a Fighter
Build a candidate pool by division, age, performance, recent activity, geography, representation and verified opportunity status.
Prospect Board
Compare emerging fighters using opponent-adjusted performance, résumé quality, age, experience and evidence strength.
Management Intelligence
Trace source-backed representation relationships and identify the best verified path for outreach.
Scout Rankings
Compare performance without allowing contract, management or recruiting status to alter the Global Rating.
Scout AI
Ask natural-language recruiting and scouting questions after structured fighter data is retrieved.
LFA 242 – LOZEJ vs. BITTENCOURT
Mystic Lake Casino Hotel · Prior Lake · MN · United States
Find the fighter. Then inspect the evidence.
Search the active UFC dataset here, then use Promotions and Scout AI for regional and global fighter research.
Division options are unavailable. Reload to try again; all-fighter rankings remain available.
How to read Scout Ratings
Scout Rating combines opponent-adjusted performance, results, schedule strength and recent form on a 0–100 scale. Category scores are normalized within each fighter’s division.
Sample strength is a 0–100 evidence index based on bout count and cage time. It is not a win probability. Fighters with limited evidence are labeled provisional.
Search preserves each fighter’s rank within the selected division and metric. “Data through” identifies the latest included event date.
Build tomorrow’s shortlist.
Regional records are more useful when you know who the wins came against and what those opponents became later.
Young undefeated fighters
Filter regional talent by age, division, wins and undefeated status.
Run the search → Opponent qualityBest-tested prospects
Rank prospects by the eventual quality and experience of the opposition they actually faced.
Run the search → Career contextWins that aged well
Find fighters whose regional wins later became more meaningful when those opponents reached the UFC.
Run the search →The AI does not get to invent the fight history.
The language model interprets the question and explains the result. MMA Scouts retrieves fighters, bouts, ratings and relationships from structured data first.
Ask about methodology →Scout AI plans a query, retrieves structured evidence, then synthesizes the answer.
Scout Ratings account for opponent quality rather than treating identical raw statistics as equally meaningful.
Small samples remain provisional, retrospective measures are labeled, and unsupported claims are supposed to be refused.
Scout AI evidence cards and fighter pages let the user inspect the records behind the explanation.