The Fight StoryClick here to expandThe story behind the stats.
Get ready for a heavyweight showdown as Tanner Boser steps into the octagon against Jhonata Diniz at UFC Fight Night: Buckley vs. Malott! Both fighters are looking to turn their fortunes around, but Diniz arrives with a notable edge in both size and finishing ability. Standing at 6'4" and weighing in at 254 pounds, Diniz has a reach advantage of 4 inches over Boser, who stands at 6'2" and weighs 205 pounds. This height and weight difference could be critical in a division where power reigns supreme.
Boser boasts a higher strike output with an impressive 22.2 significant strikes landed per round, compared to Diniz's 17.3, but Diniz compensates with a striking accuracy of 58.8%—a mark that could prove deadly if he connects. Their finish rates tell a compelling story, too: Diniz has a staggering 77.8% finish rate, compared to Boser's 60.0%. This matchup has shades of past fights like John Hathaway vs. Pascal Krauss, where a fighter with a higher finish rate made a statement, or Justine Kish vs. Ji Yeon Kim, where the striking dynamics played a pivotal role. Will Boser’s volume outpace Diniz's precision and power? The octagon awaits the answer!
Prediction IntelClick here to expandOur call — and the case for it.
Stats Model Prediction
🔒 Prediction locked in before the fight · Predicted Sep 26, 2026, 00:06 UTC
Model Breakdown
Tanner BoserJhonata Diniz
Deep Learning Model α 26% weight60.1%39.9%
Deep Learning Model ξ 25% weight57.2%42.8%
Statistical Model δ 13% weight44.9%55.1%
Statistical Model β 21% weight42.2%57.8%
Statistical Model ε 15% weight40.0%60.0%
Ensemble48.8%51.2%
AI Reasoning (why the models picked this)
Jhonata Diniz's weight advantage and higher win rate against Tanner Boser are the strongest drivers for the ensemble prediction. The ensemble favors Jhonata Diniz, despite a slight split among individual models, due to calibrated weighting.
Statistical Model β: Model β favors Jhonata Diniz, citing Jhonata Diniz's higher win rate against Tanner Boser and Tanner Boser's lower Elo rating.
Statistical Model ε: Model ε favors Jhonata Diniz, highlighting Jhonata Diniz's advantage in distance strike share, weight, and reach over Tanner Boser.
AI-generated from the model outputs above — wording may occasionally be imprecise.
Predicted Winner
Jhonata Diniz
51.2%
Confidence
* Model output, not betting advice. Bet responsibly.
Predicted Duration
3rd Round at 3m45s (13m45s total)
Chance the Fight Is Still Going
74%57%47%
Rnd 1Rnd 2Rnd 3
47%
Chance of Decision
The dashed line is 50%. The round where the curve crosses it is the round named above — the midpoint of the distribution, not necessarily its single most likely outcome.
Matchup IntelClick here to expandPast fights with a similar statistical shape, plus how fights like this one typically end.
How Similar Fights Ended
285 historical bouts
Every past fight is placed by the SHAPE of its mismatch — how far apart the two fighters were on each of 37 career measures, setting aside which one was ahead. Fights that sit close together form a profile. Below is how the 285 bouts in this bout's profile actually ended.
54%Reached the judges
46%Ended early
33%KO/TKO14%Submission5:11Median finish, round 2
When those finishes came
Rnd 166
Rnd 246
Rnd 317
Rnd 43
This is a base rate over similar past matchups, not a prediction about these two fighters. It is drawn from what happened historically, and the profile is blind to which corner is which — so it can say how fights like this one tend to go, and nothing at all about who wins.
Fights with a similar mismatch
Every fighter is reduced to a profile of 37 career measures as they stood going into the fight, standardised so that no single measure dominates merely for having bigger units — a far wider read than the six charted below. The bout is then described by the gap between the two: how far apart they were on each of those measures, setting aside which one was ahead. The fights listed here are those whose gaps line up most closely with this one. Because the match is on the shape of a mismatch rather than on a weight class or an era, a neighbour can come from an entirely different division.
84%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
84%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
82%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
82%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
82%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
80%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
80%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
80%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
80%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
79%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
79%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
79%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
79%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
79%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
78%How closely the gap between these two fighters resembles the gap in that historical bout — the size and shape of the mismatch, not the fighters themselves. Two completely different pairs can produce the same mismatch. 100% would be an identical gap; two fights picked at random score about 36%, so a number near that means there is no real comparable on record.Match
Statistics IntelClick here to expandA full head-to-head stat comparison — per-round output and career tendencies — against the UFC average.
Head-to-Head Statistics
The same per-round and advanced numbers each fighter's profile shows, side by side. The stronger value in each row is highlighted.
Stat
Tanner Boser
Jhonata Diniz
UFC AVG
Per Round Average
Strikes
21.4
14.7
13.2
Strike accuracy
54.1%
55.7%
43.9%
Takedowns
0.1
0
0.4
Takedown accuracy
75%
0%
33.0%
Sub attempts
0.0
0
0.2
Control time
39.9s
5.1s
48.9s
Knockdowns
0.07
0.07
0.08
Knockdowns absorbed
0.03
0
0.13
Advanced Fighter Statistics
win rateWins divided by this fighter's total recorded fights.
50.0%
75.0%
45.8%
recent win rateWin rate over the last 5 recorded fights only — a form signal, not a career figure.
40.0%
40.0%
37.6%
win streakCurrent run: a positive number is consecutive wins, a negative number consecutive losses.
1
-2
-2
total fightsTotal recorded fights, including bouts outside the UFC.
12
12
—
head strike shareShare of this fighter's landed significant strikes that went to the head. Head, body and leg sum to 100%.
50.2%
73.3%
—
body strike shareShare of this fighter's landed significant strikes that went to the body. Head, body and leg sum to 100%.
19.4%
6.3%
—
leg strike shareShare of this fighter's landed significant strikes that went to the legs. Head, body and leg sum to 100%.
30.5%
20.4%
—
sig strikes absorbedSignificant strikes opponents land on this fighter PER ROUND, counted from the round-by-round UFC stats across their scored rounds. Lower is better.
12.86
15.73
15.2
takedowns absorbedTakedowns opponents complete on this fighter PER ROUND, counted from the round-by-round UFC stats across their scored rounds. Lower is better.
0.24
0.73
0.4
cardio sig ratioThis fighter's significant strikes landed in the LATER rounds divided by the EARLIER rounds. 1.0 is neutral: above it their output grows late, below it they fade. Shown only for fighters with at least 3 UFC bouts on record.
0.76
0.77
0.52
cardio defence ratioWhat OPPONENTS land on this fighter in the LATER rounds divided by what they land in the EARLIER rounds. 1.0 is neutral. LOWER is better — a high value means opponents find them more as the fight wears on. Shown only for fighters with at least 3 UFC bouts on record.
0.76
1.03
0.56
cardio takedown ratioThis fighter's takedowns in the LATER rounds divided by the EARLIER rounds. 1.0 is neutral. Shown only for fighters with at least 3 UFC bouts on record.
1
0.000
0.42
is orthodoxWhether the fighter's recorded stance is orthodox.
Yes
Yes
—
is southpawWhether the fighter's recorded stance is southpaw.
No
No
—
switch stanceWhether the fighter is recorded as switching stance.
No
No
—
finish rateShare of this fighter's WINS that came by finish, KO/TKO or submission. The denominator is wins, not fights.
66.7%
77.8%
46.5%
KO win rateShare of this fighter's WINS that came by KO or TKO. The denominator is wins, not fights.
66.7%
77.8%
27.9%
sub win rateShare of this fighter's WINS that came by submission. The denominator is wins, not fights.
0.0%
0.0%
18.7%
been stopped rateShare of this fighter's LOSSES that ended by finish — the denominator is LOSSES, not fights. A fighter who is 20-1 whose single loss was a KO therefore reads 100%.
33.3%
100.0%
52.3%
distance strike shareShare of this fighter's landed significant strikes thrown at distance. Distance, clinch and ground sum to 100%.
82.9%
93.7%
—
clinch strike shareShare of this fighter's landed significant strikes thrown in the clinch. Distance, clinch and ground sum to 100%.
8.5%
3.6%
—
ground strike shareShare of this fighter's landed significant strikes thrown on the ground. Distance, clinch and ground sum to 100%.
8.5%
2.7%
—
avg fight duration (m:ss)Mean length of this fighter's UFC fights, in minutes and seconds. "—" means we hold no round-time data for them.
11:10
11:48
—
Elo ratingA UFC-only Elo rating: it rises and falls with results, weighted by the opponent's rating. 1500 is the starting and dataset-average value.
1,499.0
1,498.8
1500
PageRankHow central this fighter is in the network of who-fought-whom. It reflects the quality of opposition they have shared a cage with, not their skill.
0.075
0.065
0.069
career stageForm over the last 4 fights before this one: 3 or more wins reads Peak, 2 or fewer reads Decline, and fewer than 4 prior fights reads Early.
Decline
Decline
—
Market IntelClick here to expandHow the betting market prices this fight compared to our model's number.
Betting Edge
Fighter
Win confidence
DraftKings odds
Break-even
Edge
Tanner Boser
48.8%
2.70
37.0%
+31.7%
Jhonata Diniz
51.2%
1.49
67.1%
-23.7%
Odds are the latest we have from DraftKings. Edge = win confidence × decimal odds − 1, so a positive edge means the price pays more than our model thinks the fighter is worth.
Break-even = 1 ÷ decimal odds — the win rate you would need at that price just to come out level. It is the raw price, with the bookmaker's margin still in it, so the two fighters' break-evens add up to more than 100%: that surplus is the book's cut, not a mistake.
Recommended stakeNo bet recommended at the price we recorded.
