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: 0.0
Odds:
Josh Quinlan: -128
Adam Fugitt: +100
Josh Quinlan enters this bout on a two-fight skid, having suffered losses to Danny Barlow and Trey Waters. The knockout loss to Barlow was especially damaging, and with a quick turnaround for this matchup, there are concerns about Quinlan's ability to rebound effectively.
Despite the recent setbacks, Quinlan has shown impressive striking skills in the past. He lands 3.23 significant strikes per minute at a 40% accuracy rate. Additionally, his takedown defense is robust at 100%, although he rarely attempts takedowns himself, averaging just 0.53 per fight.
Adam Fugitt has been alternating between wins and losses in his three UFC appearances. In his most recent outing, he suffered a submission defeat against Mike Malott. However, prior to that, Fugitt showcased his knockout power by stopping Yusaku Kinoshita in an upset victory where he was a significant underdog.
Fugitt is an active wrestler, attempting 10.3 takedowns per fight with a 33% success rate. His striking defense could use improvement, as he absorbs 4.07 head strikes per minute while defending only 46.6% of the strikes thrown at him. One advantage Fugitt holds is his height and reach, enjoying a 5-inch reach advantage over Quinlan.
The model's prediction favors Josh Quinlan based on several factors:
However, some elements work in Adam Fugitt's favor:
Limited historical prediction data makes it challenging to assess the model's performance on these specific fighters. The model did incorrectly pick Fugitt over Malott in his previous bout. With no prior predictions for Quinlan, evaluating the model's accuracy is difficult, adding uncertainty to the current pick.
WolfTicketsAI predicts a Josh Quinlan victory over Adam Fugitt, albeit with a low confidence score of 0. Quinlan's striking abilities and Fugitt's inconsistent recent results are the primary factors driving this pick. However, Fugitt's wrestling skills and reach advantage could pose problems for Quinlan if the fight moves to the ground.
Both fighters are known for their aggressive styles and willingness to engage in all-out wars, which sets the stage for an exciting and potentially action-packed encounter. The betting odds suggest a competitive matchup, with Fugitt being a slight favorite according to some sportsbooks.
The quick turnaround for Quinlan following his recent knockout loss is a concern, as is the lack of historical prediction data for both fighters. These factors make this a risky fight to bet on with any real confidence. Quinlan's ability to bounce back and Fugitt's knockout power add further intrigue and unpredictability to the outcome.
Ultimately, while the model leans towards Quinlan, this shapes up as a closely contested battle that could go either way. Prudent bettors may opt to steer clear of wagering on this particular matchup given the numerous uncertainties surrounding both fighters.
Stat | Josh Quinlan | Adam Fugitt | Weight Class Average | |
---|---|---|---|---|
Main Stats | ||||
Age | 31 | 35 | 33 | |
Height | 72" | 73" | 72" | |
Reach | 72" | 77" | 74" | |
Win Percentage | 75.00% | 69.23% | 78.71% | |
Wins | 6 | 10 | ||
Losses | 3 | 4 | ||
Wins at Weight Class | 0 | 1 | ||
Losses at Weight Class | 2 | 2 | ||
Striking Stats | ||||
Striking Accuracy | 40.00% | 56.94% | 50.15% | |
Significant Striking Accuracy | 40.00% | 54.02% | 45.00% | |
Strikes Landed Per Minute | 3.234 | 5.446 | 5.449 | |
Significant Strikes Landed Per Minute | 3.234 | 4.302 | 4.157 | |
Knockdowns per Fight | 0.527 | 0.000 | 0.672 | |
Striking Impact Differential | -37.33% | 0.00% | 4.44% | |
Significant Striking Impact Differential | -36.00% | -6.00% | 3.01% | |
Striking Output Differential | -58.00% | -4.67% | 5.04% | |
Significant Striking Output Differential | -56.67% | -14.00% | 3.64% | |
Striking Defense to Offense Ratio | 217.39% | 87.39% | 86.08% | |
Significant Striking Defense to Offense Ratio | 217.39% | 110.64% | 104.59% | |
Striking Defense Percentage | 50.00% | 48.15% | 49.79% | |
Takedown and Submission Stats | ||||
Submissions per Fight | 0.000 | 0.000 | 0.541 | |
Takedowns per Fight | 0.527 | 3.433 | 1.239 | |
Takedowns Attempted per Fight | 4.745 | 10.298 | 3.387 | |
Takedown Defense | 100.00% | 100.00% | 71.85% | |
Takedown Accuracy | 11.11% | 33.33% | 34.49% | |
Head Stats | ||||
Head Strikes Landed per Minute | 1.758 | 2.288 | 2.678 | |
Head Strikes Attempted per Minute | 6.257 | 5.217 | 6.724 | |
Head Strikes Absorbed per Minute | 5.975 | 4.073 | 2.429 | |
Body Stats | ||||
Body Strikes Landed per Minute | 0.668 | 1.373 | 0.846 | |
Body Strikes Attempted per Minute | 0.879 | 1.922 | 1.195 | |
Body Strikes Absorbed per Minute | 0.703 | 0.824 | 0.786 | |
Leg Stats | ||||
Leg Strikes Landed per Minute | 0.808 | 0.641 | 0.633 | |
Leg kicks Attempted per Minute | 0.949 | 0.824 | 0.772 | |
Leg kicks Absorbed per Minute | 0.352 | 0.229 | 0.626 | |
Clinch Stats | ||||
Clinch Strikes Landed per Minute | 0.070 | 0.458 | 0.426 | |
Clinch Strikes Attempted per Minute | 0.070 | 0.641 | 0.585 | |
Clinch Strikes Absorbed per Minute | 0.070 | 0.549 | 0.389 |
Date | Weight | Elevation | Red Corner | Blue Corner | Winner |
---|---|---|---|---|---|
Feb. 17, 2024 | Welterweight | Josh Quinlan | Danny Barlow | Danny Barlow | |
April 29, 2023 | Welterweight | Josh Quinlan | Trey Waters | Trey Waters | |
Aug. 13, 2022 | Catch Weight | Jason Witt | Josh Quinlan | Josh Quinlan |
Date | Weight | Elevation | Red Corner | Blue Corner | Winner |
---|---|---|---|---|---|
June 10, 2023 | Welterweight | Mike Malott | Adam Fugitt | Mike Malott | |
Feb. 4, 2023 | Welterweight | Yusaku Kinoshita | Adam Fugitt | Adam Fugitt | |
July 30, 2022 | Welterweight | Michael Morales | Adam Fugitt | Michael Morales |