Loma Lookboonmee vs Jaqueline Amorim, UFC Fight Night: Song vs. Figueiredo prediction and deep analysis
Loma Lookboonmee/Jaqueline Amorim
Winner 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 Jaqueline Amorim (65% win probability).
- Suphisara Konlak path. "Volume-pressure decision": Close distance behind combinations to nullify reach
- Jaqueline Amorim path. "Early submission chain": Find clinch or reactive takedown entries in opening round
- Risk: Opponent identity uncertainty
- Risk: Reach-tax exhaustion
Frequently Asked Questions
Who won Loma Lookboonmee vs Jaqueline Amorim?
Jaqueline Amorim won. Blueprint MMA's pre-fight pick was Jaqueline Amorim.
Who wins Loma Lookboonmee vs Jaqueline Amorim?
Blueprint MMA's War Room Committee picks Jaqueline Amorim with a 65% win probability.
What could change the outcome of Loma Lookboonmee vs Jaqueline Amorim?
Opponent identity uncertainty: The unresolved discrepancy between listed opponent Loma Lookboonmee and analyzed opponent Suphisara Konlak degrades confidence in all matchup-specific signals; tactical reads may not map to the actual cage pairing. Reach-tax exhaustion: Konlak's severe reach and height deficits force repeated distance-closing against a longer fighter; if this tax accumulates, her pressure volume drops and Amorim's entry windows expand. Injury-related ring rust: Amorim's extended layoff was injury-related rather than camp-cycle standard, creating variance in timing and grappling sharpness that could delay her submission chain.
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.