The content below shows how the model reached its conclusion for the prediction. The higher the value of the number, the more confident the model is in the prediction. The confidence scores do not perfectly correlate with accuracy. Use your judgement to see where the model may have missed the mark.
Basic Prediction
This prediction was made before July 20th, 2024 and does not include detailed insights.
Score: 20 Odds: Luana Santos: -375 Mariya Agapova: 290
Luana Santos, a rising star with a 7-1 record, brings a well-rounded skill set to this flyweight clash. Her orthodox stance and 67-inch reach have been effective tools in maintaining distance and controlling fights. Santos's striking accuracy of 55% demonstrates her precision, while her recent KO/TKO victory over Juliana Miller showcases her finishing ability.
Training with Team Alpha Male has significantly enhanced Santos's grappling prowess, complementing her three career submission victories. Her recent unanimous decision win against Stephanie Egger proves she can go the distance against tough opposition.
A crucial factor in Santos's preparation is her management of Hashimoto's disease, an autoimmune condition affecting her thyroid. After a significant weight miss in her previous bantamweight bout, Santos claims the condition is now under control, allowing her to make the flyweight limit for this fight.
Mariya "Demonslayer" Agapova enters the octagon with a 10-4 record and a diverse skill set. Her southpaw stance and slightly longer 68.5-inch reach could pose interesting challenges for Santos. Agapova's striking power is evident in her three TKO victories, while her ground game remains her most significant threat, with five of her ten wins coming by submission.
However, Agapova faces momentum challenges, currently on a two-fight losing streak with her last bout in 2022 ending in a submission loss. Personal and financial difficulties have also plagued Agapova, potentially impacting her mental state entering this crucial fight.
The model correctly predicted Santos's victory over Stephanie Egger (score 0.72), adding credibility to the current prediction. However, it has limited data on Santos, with only one previous prediction.
For Agapova, the model's track record is less reliable, incorrectly predicting her victories against both Gillian Robertson and Maryna Moroz. This inconsistency adds uncertainty to the current prediction.
The data and model prediction favor Luana Santos in this women's flyweight bout. Her superior striking defense, recent form, and the betting market's confidence all point towards a Santos victory. Santos will likely aim to keep the fight standing, leveraging her striking accuracy and power.
However, Agapova's submission threat and southpaw stance present unique challenges. The contrast in recent career trajectories - Santos's rise vs Agapova's struggles - adds an intriguing narrative layer to this matchup.
While the prediction seems solid, Agapova's unpredictability and the model's past inaccuracies with her fights suggest caution. This bout promises to be a compelling clash of styles and career narratives in the women's flyweight division.
Stat | Luana Santos | Mariya Agapova | Weight Class Average | |
---|---|---|---|---|
Main Stats | ||||
Age | 24 | 27 | 31 | |
Height | 66" | 66" | 65" | |
Reach | 67" | 68" | 66" | |
Win Percentage | 87.50% | 71.43% | 75.87% | |
Wins | 8 | 10 | ||
Losses | 1 | 5 | ||
Wins at Weight Class | 1 | 2 | ||
Losses at Weight Class | 0 | 3 | ||
Striking Stats | ||||
Striking Accuracy | 60.30% | 67.91% | 49.49% | |
Significant Striking Accuracy | 55.50% | 57.35% | 42.19% | |
Strikes Landed Per Minute | 8.617 | 9.643 | 5.807 | |
Significant Strikes Landed Per Minute | 6.209 | 5.530 | 3.910 | |
Knockdowns per Fight | 0.000 | 0.834 | 0.122 | |
Striking Impact Differential | 12.00% | 34.20% | 4.67% | |
Significant Striking Impact Differential | 24.00% | 14.00% | 4.05% | |
Striking Output Differential | -1.50% | 32.20% | 5.96% | |
Significant Striking Output Differential | 9.50% | 12.80% | 5.28% | |
Striking Defense to Offense Ratio | 82.61% | 50.14% | 82.23% | |
Significant Striking Defense to Offense Ratio | 105.17% | 77.39% | 109.40% | |
Striking Defense Percentage | 64.21% | 54.42% | 50.41% | |
Takedown and Submission Stats | ||||
Submissions per Fight | 0.000 | 1.251 | 0.587 | |
Takedowns per Fight | 1.606 | 0.834 | 1.438 | |
Takedowns Attempted per Fight | 3.211 | 0.834 | 3.238 | |
Takedown Defense | 50.00% | 100.00% | 67.25% | |
Takedown Accuracy | 50.00% | 100.00% | 37.45% | |
Head Stats | ||||
Head Strikes Landed per Minute | 3.426 | 3.585 | 2.472 | |
Head Strikes Attempted per Minute | 7.654 | 7.114 | 6.728 | |
Head Strikes Absorbed per Minute | 2.462 | 2.168 | 2.144 | |
Body Stats | ||||
Body Strikes Landed per Minute | 2.034 | 1.556 | 0.879 | |
Body Strikes Attempted per Minute | 2.623 | 2.029 | 1.238 | |
Body Strikes Absorbed per Minute | 1.178 | 0.806 | 0.828 | |
Leg Stats | ||||
Leg Strikes Landed per Minute | 0.749 | 0.389 | 0.559 | |
Leg kicks Attempted per Minute | 0.910 | 0.500 | 0.701 | |
Leg kicks Absorbed per Minute | 0.000 | 0.611 | 0.580 | |
Clinch Stats | ||||
Clinch Strikes Landed per Minute | 0.696 | 0.862 | 0.445 | |
Clinch Strikes Attempted per Minute | 1.392 | 1.084 | 0.614 | |
Clinch Strikes Absorbed per Minute | 1.124 | 0.417 | 0.459 |
Date | Weight | Elevation | Red Corner | Blue Corner | Winner |
---|---|---|---|---|---|
Dec. 9, 2023 | Women's Bantamweight | Luana Santos | Stephanie Egger | Luana Santos | |
Aug. 12, 2023 | Women's Flyweight | Juliana Miller | Luana Santos | Luana Santos |
Date | Weight | Elevation | Red Corner | Blue Corner | Winner |
---|---|---|---|---|---|
Sept. 17, 2022 | Women's Flyweight | Mariya Agapova | Gillian Robertson | Gillian Robertson | |
March 5, 2022 | Women's Flyweight | Maryna Moroz | Mariya Agapova | Maryna Moroz | |
Oct. 9, 2021 | Women's Flyweight | Sabina Mazo | Mariya Agapova | Mariya Agapova | |
Aug. 22, 2020 | Women's Flyweight | Mariya Agapova | Shana Dobson | Shana Dobson | |
June 13, 2020 | Women's Flyweight | Mariya Agapova | Hannah Cifers | Mariya Agapova |