UFC Fight Night: Du Plessis vs Usman: Model Analysis
Event: UFC Fight Night: Du Plessis vs Usman Posted: July 14, 2026 · VAR Research First fight: July 19 2026, 00:00 UTC Card scope: 11 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.
Anna Melisano vs Dione Barbosa. Public consensus implies Anna Melisano at 22.1%. Our model projects 57.5%. A 35-point gap, with Anna Melisano materially underrated by the market.
RJ Harris vs Alvin Hines. Public consensus implies RJ Harris at 45.7%. Our model projects 73.5%. A 28-point gap, with RJ Harris materially underrated by the market.
Full card projection
| Matchup | Projection | Confidence |
|---|---|---|
| Dricus Du Plessis vs Kamaru Usman | Dricus Du Plessis 57.2% | Medium |
| Jared Cannonier vs Christian Leroy Duncan | Christian Leroy Duncan 78.3% | High |
| Chase Hooper vs Mitch Ramirez | Chase Hooper 83.0% | High |
| Tabatha Ricci vs Fatima Kline | Fatima Kline 57.8% | Medium |
| Tommy McMillen vs Alberto Montes | Tommy McMillen 73.7% | High |
| Austin Bashi vs Jose Miguel Delgado | Jose Miguel Delgado 54.5% | Coin flip |
| Jean-Paul Lebosnoyani vs Seokhyeon Ko | Seokhyeon Ko 57.6% | Medium |
| Levi Rodrigues Jr. vs Felipe Franco | Levi Rodrigues Jr. 64.7% | Medium |
| Alden Coria vs Stewart Nicoll | Alden Coria 81.4% | High |
| RJ Harris vs Alvin Hines | RJ Harris 73.5% | High |
| Anna Melisano vs Dione Barbosa | Anna Melisano 57.5% | Medium |
Matchup notes
Dricus Du Plessis vs Kamaru Usman. Dricus Du Plessis outpaces Kamaru Usman on strike volume (5.2 vs 4.2 per minute).
Jared Cannonier vs Christian Leroy Duncan. Striker-vs-striker matchup, with Christian Leroy Duncan’s accuracy edge (57% vs 49%) doing the work. Christian Leroy Duncan absorbs notably less (3.0 vs 4.3 per minute), projecting better damage profile through three rounds.
Chase Hooper vs Mitch Ramirez. Chase Hooper holds the takedown-rate edge (2.5 vs 0.6 per 15 min).
Tabatha Ricci vs Fatima Kline. Fatima Kline absorbs notably less (2.7 vs 5.2 per minute), projecting better damage profile through three rounds.
Tommy McMillen vs Alberto Montes. Tommy McMillen brings the cleaner striking and credible takedown defense (83%) to keep the fight standing. Tommy McMillen outpaces Alberto Montes on strike volume (7.5 vs 5.0 per minute).
Austin Bashi vs Jose Miguel Delgado. Style symmetry between Jose Miguel Delgado and Austin Bashi. The model declines to favor either side beyond noise.
Jean-Paul Lebosnoyani vs Seokhyeon Ko. Seokhyeon Ko absorbs notably less (1.4 vs 3.7 per minute), projecting better damage profile through three rounds.
Levi Rodrigues Jr. vs Felipe Franco. Levi Rodrigues Jr. brings the cleaner striking and credible takedown defense (100%) to keep the fight standing. Levi Rodrigues Jr. outpaces Felipe Franco on strike volume (4.5 vs 2.2 per minute).
Alden Coria vs Stewart Nicoll. Alden Coria absorbs notably less (2.4 vs 6.7 per minute), projecting better damage profile through three rounds.
RJ Harris vs Alvin Hines. Model projects RJ Harris (73.5%) over Alvin Hines; thin career data on both sides limits the narrative beyond the projection itself.
Anna Melisano vs Dione Barbosa. Model projects Anna Melisano (57.5%) over Dione Barbosa; thin career data on both sides limits the narrative beyond the projection itself.
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.