As the UFC continues its calendar with UFC Vegas 113 this Saturday at the newly named META APEX, the focus turns to key matchups where data-driven insights highlight potential outcomes. The model, currently riding a solid 10-3 run for the year, singles out the main event as a stage for a significant upset, predicting an underdog victory that could surprise many fans and bettors alike.
This event, headlined by Mario Bautista facing Vinicius Oliveira, marks the first non-title Fight Night of the year, kicking off a stretch of several such cards. Though betting activity might be lighter over the coming weeks, the model identifies value opportunities by analyzing fighter metrics and tendencies, guiding bettors through an uncertain landscape.
Flyweight Clash: Cong Wang Against Eduarda Moura
The card opens with a competitive flyweight battle between Cong Wang, nicknamed The Joker, and Eduarda Moura, both standing 3-1 in their UFC careers. Wang arrives on a two-fight winning streak and has been favored in every UFC appearance so far, backed by an exceptional expected strike rate (xR%) of 86%, one of the highest figures on this fight card.
Moura also brings momentum, having won her last two fights, most notably an impressive victory over Lauren Murphy. However, questions shadow her transition to flyweight after missing weight twice at strawweight; this will be her third fight at the heavier division. The matchup appears challenging given her style versus Wang’s strengths.
Statistically, the contrast is evident. Wang is primarily a distance striker, spending 98% of her fight time at range and landing 7.58 significant strikes per minute while absorbing only 2.84. This creates a remarkable +4.74 strike differential that speaks to her dominant striking output and defense.
Meanwhile, Moura fires less than half as many strikes per minute (3.16) with a 38% accuracy rate, significantly lower than Wang’s 56%. Moura’s path to victory likely depends on using her control and pressure to negate Wang’s striking. Across four UFC bouts, Moura has recorded 13 takedowns and controls 85% of her clinch and ground time, launching an average of 6.2 takedown attempts every five minutes.
However, Wang’s takedown defense is outstanding, having successfully defended all seven takedown attempts against her in the UFC. Whether Moura can force enough ground exchanges to make this strategy effective remains the central question.
The predictive model assigns Wang an 82.27% chance of winning, closely reflecting the general betting odds near -340. While this lowers the appeal of a straight bet on her, Wang remains a solid choice for parlay combinations. For bettors seeking prop bets, options present themselves: Wang by decision is around -110 odds, whereas Wang by KO/TKO at +400 could be a lucrative underdog wager given her striking edge.
Control-Oriented Flyweight Battle: Jean Matsumoto Versus Farid Basharat
This flyweight matchup contrasts dominance with meticulous control. Jean Matsumoto, coming off a decision win over Miles Johns, shows promise but exhibits weaknesses shown in his 45% expected round win rate despite a 3-1 UFC record. This suggests he has not clearly dominated rounds even in victory—a potential vulnerability against a precise opponent.
Farid Basharat enters undefeated at 14-0 overall and 5-0 in the UFC, maintaining a strong xR% of 76%. His latest triumph came via decision over Chris Gutierrez in October. Basharat is not a high-volume striker but applies pressure and strategic breaking down of opponents over time.
Matsumoto lands 5.09 significant strikes per minute but absorbs nearly as many, resulting in a negligible strike differential of -0.02. Basharat throws fewer strikes (3.19 per minute) but is more efficient, holding a +0.56 differential alongside a 69% head strike defense, indicating his ability to avoid damage.
Basharat’s strengths extend beyond striking; he controls 85% of his clinch and ground time and boasts 16 takedowns with a 44% success rate—placing fights firmly on his terms. Matsumoto’s takedown defense, conversely, is a notable liability, having been taken down 17 times in just four UFC fights, with a defense rate of only 51%.
The model predicts Basharat to win 76.09% of the time, mirroring his market odds of about -275. Though close enough to discourage a confident single bet, Basharat by decision at roughly -140 odds emerges as an attractive props bet. Given his technician style and Matsumoto’s resilience despite difficulties, the fight is likely to last the distance with Basharat controlling tempo and position.
Main Event Spotlight: Mario Bautista Versus Vinicius Oliveira
Saturday’s headliner offers a compelling test for both combatants. Mario Bautista looks to rebound from a decision loss to Umar Nurmagomedov, a result that carried no embarrassment despite setbacks. Bautista enters with a solid UFC history, having defeated recognizable fighters like Ricky Simon, Patchy Mix, and a late-career Jose Aldo. With 13 UFC bouts behind him, this fight may reveal whether his trajectory is still upward or leveling off.
Opposite Bautista stands Vinicius “Lok Dog” Oliveira, a UFC undefeated six-fight streak holder with 18 career finishes, 16 of which are knockouts. He recently secured a solid decision victory over Kyler Phillips. Oliveira’s surface record may not be as polished as Bautista’s, but his performance metrics are impressive, including an xR% at 67%, slightly above Bautista’s 61%.
Technology metrics highlight the striking battle. Bautista averages 5.58 significant strikes per minute, with Oliveira close behind at 5.06. Efficiency sets Oliveira apart—he carries a +2.14 strike differential, demonstrating the ability to land hard shots while minimizing absorbed damage, outpacing Bautista’s respectable +1.40 figure.
Adding to Oliveira’s threat are his power punches; he has knocked Bautista down twice in UFC fights, signaling serious finishing potential to disrupt the contest. Grappling exchanges could also influence the match’s outcome. Oliveira controls 65% of clinch and ground time, securing 7 takedowns with 50% accuracy, while Bautista has 13 takedowns at just 32% efficiency and defends takedowns at a 55% rate, suggesting potential vulnerability.
The model gives Oliveira a 68.41% chance of winning, offering great value compared to market prices that opened around +175 but have since dipped toward +150. This makes Oliveira a rare live underdog pick in the main event that reflects genuine opportunity rather than just wishful thinking. His youth and powerful arsenal may be set to overwhelm the more experienced Bautista at this pivotal moment in both fighters’ careers.
Wider Betting Landscape and Strategic Considerations
With UFC Vegas 113 marking an early segment of fight nights, the model’s current strength in prediction suggests careful but selective engagement in betting markets. Despite last week’s mostly chalk-favored outcomes, this weekend shines a spotlight on Oliveira as a standout underdog prospect, reminding bettors to adhere to analytics over bias.
The numbers-driven approach continues to prioritize matchups where statistical advantages highlight edges in striking efficiency, takedown defense, and control, reducing guesswork in an arena often dominated by volatility and upsets.
For deeper insights and analysis, the “First Strike” podcast offers in-depth previews and betting discussions. This week’s episode features Kyle Anthony of WagerTalk, providing listeners with expert perspectives to complement data-led models. Fans can access the podcast on YouTube and all major podcast platforms, ensuring ongoing engagement with the sport’s evolving narratives.
Following experts like @TheRobbeo and @drosssports on social media platforms helps keep track of model updates, insider info, and last-minute betting tips ahead of future UFC events.
As UFC Vegas 113 unfolds, the model’s predictions set the stage for intriguing battles that balance experience, power, and tactical skill, delivering both expected outcomes and surprising developments in the octagon.
Current Win Probability Estimates by the Model
- Vinicius Oliveira: 68.41%
- Kyoji Horiguchi: 69.47%
- Michal Oleskiejczuk: 78.81%
- Farid Basharat: 76.09%
- Ketlen Souza: 66.65%
- Said Nurmagomedov: 53.69%
- Cong Wang: 82.27%
Bolded fighters indicate those the model strongly favors.
