Disclaimer:
The information presented here is strictly for informational and analytical purposes only. It does not constitute betting advice, financial advice, or a recommendation to place any wagers. All insights and predictions are based on data analysis and do not guarantee any outcomes. Please gamble responsibly and consult a professional advisor if you need financial guidance.


This is a fascinating veteran-versus-surging-contender matchup. Belal remains one of the best minute-winners in the division. His pressure, cage control, cardio, and tactical discipline have historically neutralized dangerous finishers. Even after losing the title, his skill set remains extremely difficult to deal with for fighters who rely on explosive moments.
Bonfim presents a different challenge than many of Belal’s previous opponents. His submission threat is legitimate at every stage of the fight. The UFC prediction model’s newer Opportunistic Submission Volatility (OSV) and Submission Volatility Expansion (SVE) factors raise Bonfim’s upset potential because he does not require prolonged control to find a finish. One scramble can end the fight.
Belal’s path is clear: pressure Bonfim, force extended wrestling exchanges, wear on his gas tank, and bank rounds through control and volume. Bonfim’s path is also clear: capitalize on transitions, catch a submission during scrambles, or hurt Belal early before the fight settles into a grinding pace.
The major concern for Bonfim is sustainability. The model’s Prospect Sustainability Gate (PSG) applies here because he has not consistently demonstrated five-round pace against elite opposition. Belal has repeatedly proven he can maintain pressure deep into championship rounds.
The major concern for Belal is age and mileage. Recent model updates have increased respect for younger, explosive contenders facing aging veterans. However, Bonfim is still relatively untested against someone with Belal’s level of wrestling intelligence, composure, and championship experience.
Belal’s ability to neutralize dangerous grapplers, maintain positional discipline, and consistently win minutes gives him the edge, but this is much closer than many of his past fights because Bonfim possesses genuine finishing danger throughout the contest.
Most Likely Outcome: Belal Muhammad by Decision (Rounds 4–5 dominance after competitive early rounds)
Confidence Level: Moderate
Volatility Rating: 0.61 (higher than a typical Belal fight due to Bonfim’s submission threat)


This matchup strongly favors Allen’s style. Shahbazyan remains one of the division’s more dangerous early finishers, but many of his career losses have followed a familiar pattern: opponents survive the early storm, increase pressure, and force him into difficult grappling and cardio-intensive situations.
Allen’s game is specifically built to exploit those weaknesses. His wrestling entries, clinch work, scrambling ability, and submission chains create constant problems for opponents who struggle once the fight becomes messy. The model’s Control Undervaluation Fix, Grappling Fallback Weight, and Early Control Lock Rule all favor Allen if he establishes top position early.
Shahbazyan still carries meaningful knockout equity. The model’s Power Threat Preservation (PTP) prevents overlooking his finishing ability simply because Allen is the more complete fighter. Edmen remains fast, athletic, and dangerous enough to end the fight if Allen enters recklessly or absorbs clean counters during takedown attempts.
However, Allen has consistently shown better durability, superior cardio, and stronger adversity response against higher-level opposition. The Cardio Sustain Index (CSI) and Composure Under Pressure Modifier (CUPM) both favor Allen. When fights extend beyond the opening round, Allen historically becomes stronger while Shahbazyan’s effectiveness often declines.
Another important factor is Allen’s recent victory over Marvin Vettori. While Vettori and Shahbazyan are different stylistic matchups, Allen demonstrated improved patience, fight IQ, and ability to win rounds without forcing mistakes. The model’s Adaptive Bounce Factor (ABF) and Gameplan Discipline Bonus (GDB) give him additional credit for that evolution.
For Shahbazyan to win, he likely needs a damaging early striking sequence or a knockout within the first two rounds. If Allen survives the initial danger and begins forcing grappling exchanges, the fight increasingly shifts in his favor with every passing minute.
Most Likely Outcome: Brendan Allen by Submission
Confidence Level: Moderately High
Volatility Rating: 0.53
Edmen’s early knockout threat prevents this from being a high-confidence pick, but Allen’s grappling, cardio, durability, and proven ability against stronger competition make him the deserved favorite.


This is a classic matchup between a proven technical minute-winner and a younger, more explosive athlete. The model views Nolan as the more dangerous finisher, but Ziam as the more reliable overall fighter.
Ziam has quietly become one of the better range-control specialists in the lightweight division. His movement, kicking game, and ability to stay disciplined over three rounds make him difficult to pressure effectively. The model’s Gameplan Discipline Bonus (GDB) and Adaptive Technician Bonus (ATB) favor Ziam because he consistently follows structured game plans and makes adjustments during fights.
Nolan possesses the more dangerous physical tools. The Power and Physicality Adjustment (PPA) and Damage & Physicality Override (DPO v2) both increase his upset potential. At lightweight, Nolan’s size, reach, and finishing ability are legitimate weapons. He can change the fight with a single clean shot, which keeps his win probability higher than a typical prospect facing a ranked-level technician.
However, Nolan remains somewhat unproven against opponents with Ziam’s composure and defensive responsibility. The model’s Prospect Sustainability Gate (PSG) and Prospect Record Reliability Filter (PRRF) apply here. Nolan has shown impressive offensive performances, but he has not consistently demonstrated that he can maintain effectiveness when opponents deny his preferred rhythm and force him into a technical fight.
A key factor is Ziam’s ability to neutralize chaos. Recent model updates emphasize determining who actually wins minutes within chaotic exchanges rather than simply favoring the more aggressive fighter. Ziam’s counter-striking, distance management, and patience suggest he can force Nolan into lower-volume rounds where technical scoring becomes more important than raw power.
Nolan’s best path is to pressure early, force exchanges, and make the fight physical before Ziam establishes his preferred range. If he allows Ziam to dictate distance and tempo, the fight could resemble many of Ziam’s recent victories where he steadily accumulates rounds through cleaner, more efficient striking.
The model also applies the Finish Threat vs Win Probability Separation (FTWPS) correction. Nolan may have the higher finish probability, but that does not automatically translate into a higher overall win probability. Over fifteen minutes, Ziam’s consistency, experience, and technical discipline provide the stronger baseline.
Most Likely Outcome: Fares Ziam by Decision
Confidence Level: Moderate
Volatility Rating: 0.58
Nolan’s power, athleticism, and finishing upside make him a live underdog, but Ziam’s superior technical consistency, range control, and proven ability to win rounds against quality opposition give him a slight edge.


This matchup largely comes down to whether Luna can keep the fight standing. Mitchell remains one of the strongest control grapplers at featherweight despite some recent setbacks. His wrestling entries, chain takedowns, back-taking ability, and positional control create problems for almost anyone outside the elite tier of the division.
The model’s Early Control Lock Rule (ECLR) strongly favors Mitchell. If he establishes top position early, his ability to accumulate control time and force defensive grappling exchanges significantly increases his probability of winning rounds and finding submission opportunities.
Luna is the less proven fighter and triggers several model caution flags, including the Prospect Sustainability Gate (PSG) and Data Completeness Flag (DCF). There is simply less high-level evidence regarding how he responds when an elite grappler repeatedly forces him into difficult positions. Unknown prospects can be dangerous, but uncertainty also reduces confidence in projecting them against proven UFC veterans.
One area where the model has become more cautious is assuming wrestling dominance automatically translates to victory. The Grappling Reliability Collapse Rule (GRCR) and Matchup-Specific Grappling Validation (MSGV) require evidence that a grappler can still consistently execute against resistance. Mitchell passes those checks. His wrestling remains functional at UFC level, and his style has historically translated well against opponents who lack elite takedown defense.
Luna’s best path is to make the fight chaotic on the feet before Mitchell settles into his wrestling rhythm. The model’s Chaos Conversion Rule (CCR) and Power Threat Preservation (PTP) acknowledge that younger, aggressive fighters can create volatility even when they are technically outmatched. If Luna hurts Mitchell early or punishes entries with clean counters, the fight becomes much more competitive.
However, Mitchell’s experience advantage is substantial. He has spent years competing against UFC-level athletes and has repeatedly demonstrated the ability to recover from adversity, maintain grappling pressure, and execute a clear game plan. The Veteran Counter-Composure Restoration (VCCR) and Gameplan Discipline Bonus (GDB) both favor him.
Unless Luna demonstrates elite takedown defense and scramble resistance, Mitchell’s wrestling should eventually dictate where the fight takes place. Once the fight consistently hits the mat, the matchup shifts heavily toward Mitchell.
Most Likely Outcome: Bryce Mitchell by Submission
Confidence Level: Moderately High
Volatility Rating: 0.47
Mitchell’s grappling edge, UFC experience, and proven ability to control fights make him one of the stronger favorites on this card. Luna has upset potential through athleticism and early offense, but Mitchell’s path to victory is clearer and more repeatable.


This is a high-volatility heavyweight matchup where finishing potential outweighs technical consistency. Heavyweight fights already trigger the model’s Heavyweight Volatility Amplifier (HVA), which prevents excessive confidence because a single exchange can completely change the outcome.
Tafa’s biggest advantage is proven UFC-level striking power. The model’s Power Threat Preservation (PTP), Damage & Physicality Override (DPO v2), and Explosive Finisher Priority Override (EFPO) all push this matchup toward the fighter with demonstrated knockout ability. Tafa has shown that his power translates against UFC competition, which is valuable compared to a prospect still proving himself.
Baraniewski benefits from the model’s Unknown Finisher Adjustment (UFA) and Prospect Reality Upgrade (PRU). The model no longer automatically discounts aggressive prospects simply because they lack UFC experience. If a prospect shows legitimate finishing ability and athleticism, volatility increases rather than defaulting toward the veteran.
The concern for Tafa is that many of his MMA victories have relied heavily on striking exchanges. The model’s Glove Transition Volatility (GTV) and Data Completeness Flag (DCF) remain relevant whenever a fighter’s overall MMA game is less proven than their striking credentials. If Baraniewski can force clinch exchanges, wrestling, or extended grappling sequences, Tafa becomes significantly less comfortable.
However, there is currently more evidence supporting Tafa’s ability to hurt opponents than there is supporting Baraniewski’s ability to consistently exploit Tafa’s grappling weaknesses. The model’s Market Sanity Check (MSC)also favors the proven UFC athlete unless a clear stylistic edge exists for the underdog.
Another important factor is the Prospect Sustainability Gate (PSG). While Baraniewski may have upside, there is less evidence regarding how he performs under UFC-level pressure, after taking damage, or when forced into difficult adjustments mid-fight.
At heavyweight, proven power remains one of the most predictive attributes. Tafa has demonstrated that power repeatedly. Unless Baraniewski can survive the early danger and consistently make the fight ugly with clinch work or wrestling pressure, Tafa’s striking advantage is likely to become decisive.
Most Likely Outcome: Junior Tafa by KO/TKO
Confidence Level: Moderate
Volatility Rating: 0.68
This is one of the more volatile fights on the card. Tafa has the clearer finishing path and more proven UFC-level power, but heavyweight chaos and limited information on Baraniewski prevent this from becoming a high-confidence pick.