UFC Fight Night: Song vs Figueiredo: Model Analysis
Event: UFC Fight Night: Song vs Figueiredo Posted: May 26, 2026 · VAR Research First fight: May 30 2026, 11:00 UTC Card scope: 10 fights, lines locked at posted time Methodology: Methodology Model accuracy: Performance
Where the model diverges from consensus
Two matchups show the largest gap between our projected win probability and the public consensus.
Cameron Smotherman vs Kai Asakura. Public consensus implies Cameron Smotherman at 30.6%. Our model projects 62.6%. A 32-point gap, with Cameron Smotherman materially underrated by the market.
Tallison Teixeira vs Sergei Pavlovich. Public consensus implies Tallison Teixeira at 14.2%. Our model projects 30.0%. A 16-point gap, with Tallison Teixeira materially underrated by the market.
Full card projection
| Matchup | Projection | Confidence |
|---|---|---|
| Song Yadong vs Deiveson Figueiredo | Song Yadong 71.6% | High |
| Zhang Mingyang vs Alonzo Menifield | Zhang Mingyang 58.3% | Medium |
| Sergei Pavlovich vs Tallison Teixeira | Sergei Pavlovich 70.0% | High |
| Kai Asakura vs Cameron Smotherman | Cameron Smotherman 62.6% | Medium |
| Muslim Salikhov vs Jake Matthews | Jake Matthews 59.7% | Medium |
| Alex Perez vs Sumudaerji | Sumudaerji 55.7% | Medium |
| Aoriqileng vs Cody Haddon | Cody Haddon 66.3% | High |
| Rei Tsuruya vs Jesus Aguilar | Rei Tsuruya 63.8% | Medium |
| Angela Hill vs Jingnan Xiong | Jingnan Xiong 60.8% | Medium |
| Loma Lookboonmee vs Jaqueline Amorim | Loma Lookboonmee 67.2% | High |
Matchup notes
Song Yadong vs Deiveson Figueiredo. Song Yadong brings the cleaner striking and credible takedown defense (73%) to keep the fight standing. Song Yadong outpaces Deiveson Figueiredo on strike volume (4.4 vs 2.6 per minute).
Zhang Mingyang vs Alonzo Menifield. Zhang Mingyang outpaces Alonzo Menifield on strike volume (7.7 vs 3.8 per minute).
Sergei Pavlovich vs Tallison Teixeira. Sergei Pavlovich enters 4-1 in his last 5; Tallison Teixeira is 2-1. Recent-form trajectory tilts the matchup. Sergei Pavlovich’s takedown defense (75%) is the largest gap on the board against Tallison Teixeira’s (0%).
Kai Asakura vs Cameron Smotherman. Cameron Smotherman outpaces Kai Asakura on strike volume (4.1 vs 2.3 per minute).
Muslim Salikhov vs Jake Matthews. Model projects Jake Matthews (59.7%) over Muslim Salikhov; thin career data on both sides limits the narrative beyond the projection itself.
Alex Perez vs Sumudaerji. Sumudaerji absorbs notably less (2.4 vs 3.2 per minute), projecting better damage profile through three rounds.
Aoriqileng vs Cody Haddon. Cody Haddon outpaces Aoriqileng on strike volume (9.2 vs 4.7 per minute).
Rei Tsuruya vs Jesus Aguilar. Rei Tsuruya holds the takedown-rate edge (5.1 vs 1.6 per 15 min).
Angela Hill vs Jingnan Xiong. Model projects Jingnan Xiong (60.8%) over Angela Hill; thin career data on both sides limits the narrative beyond the projection itself.
Loma Lookboonmee vs Jaqueline Amorim. Loma Lookboonmee outpaces Jaqueline Amorim on strike volume (3.7 vs 2.4 per minute).
How to read this
Projections come from VAR’s production UFC ensemble model, refreshed nightly. The model combines fighter performance metrics, simulation-based fight modeling, and historical opponent-strength signal, with conservative treatment of fighters who have limited recent data.
Confidence labels reflect projection spread:
- High: pick probability above 65%
- Medium: pick probability between 55 and 65%
- Coin flip: pick probability below 55%
Note: this analysis does not incorporate fight-week intelligence such as late injury reports or weight cut difficulty. Those signals are tracked through a separate process.
Model accuracy
Cross-validated across 3 independent test seasons in our 2026-04-30 audit:
- Straight-up winner accuracy across all fights: 76.7%
- Highest-confidence subset (n=207): 69.1% directional accuracy, 95% confidence interval [62.5%, 75.0%]
Full validation methodology and per-season breakdowns: Methodology.
Results
Populates after card concludes.
For research and informational purposes only. Probabilities reflect model output and may diverge from realized outcomes.
Results pending. Graded after the card concludes.