Shauna Bannon vs Nicolle Caliari, UFC Fight Night: Allen vs. Costa prediction and deep analysis
Shauna Bannon/Nicolle Caliari
Women's StrawweightWinner Committee
Thirty-three specialists answer distinct winner-only questions. Eligible evidence is renormalized only inside its original lane.
Fight-State Projection
These are distributions of eligible committee signal mass—not invented percentages of fight time.
Conditional Method Model
Each row is conditional on that fighter already winning; every fighter row sums to 100%.
Conditional Round Model
Round-event mass is derived from survival-conditioned hazards. The final scheduled round is absorbing.
Probability Reconciliation
The exact-outcome grid preserves both winner marginals and sums to 100%. Decision branches have no round.
Output Selection
The winner and every outcome label come from one immutable reconciled distribution. Oversight may widen uncertainty, never move the point forecast.
Key Takeaways
- The War Room Committee picks Shauna Bannon (71% win probability).
- Shauna Bannon path. "Volume accumulation decision": Establish jab volume from range early
- Nicolle Caliari path. "Early takedown-to-submission": Close distance behind feints to hide level changes
- Risk: Unquantified wrestling efficacy
- Risk: Submission vulnerability swing
Frequently Asked Questions
Who won Shauna Bannon vs Nicolle Caliari?
Nicolle Caliari won. Blueprint MMA's pre-fight pick was Shauna Bannon.
Who wins Shauna Bannon vs Nicolle Caliari?
Blueprint MMA's War Room Committee picks Shauna Bannon with a 71% win probability.
What could change the outcome of Shauna Bannon vs Nicolle Caliari?
Unquantified wrestling efficacy: Caliari's takedown entries against Bannon's switch stance are theoretically threatening but lack historical delta confirmation; if entries fail, Bannon's volume edge widens. Submission vulnerability swing: Bannon has been submitted in two of her last four recorded bouts; one clean takedown-to-back sequence flips the read entirely. Control-time scoring gap: Caliari's brief average control periods may not register with judges even if takedowns land, leaving her dependent on finishes.
How does Blueprint MMA make this prediction?
Blueprint MMA validates and freezes the fight data, then runs 68 Kimi K2.6 agent executions: 33 Winner, 10 Method, 20 Timing, and 5 non-voting Oversight. Kimi K2.6 is the only inference model; LangGraph only orchestrates stage order and state. Winner agents fix the point probability first, Method and Timing agents fill conditional branches without reopening it, and Oversight audits without voting. The public probability is held to a sane 5-95% range and logged before release. Published winner probabilities are AI-only. Market prices may be shown for benchmarking, CLV, and workflow context, but they do not select, rank, or alter the published forecast. If the direct pipeline cannot return a valid read, the forecast is held. Methodology is documented at https://blueprintmma.com/manifesto and accuracy is tracked publicly at https://blueprintmma.com/track-record.