FightChoice Intelligence Report

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Francis Marshall vs Dakota Hope

https://fightchoice.app/events/francis-marshall-vs-dakota-hope-prediction-2026-10-31

Featherweight

UFC Fight Night: Moicano vs. Nolan · Oct 31, 2026

In This Report

The Fight StoryClick here to expand

As featherweights Francis Marshall and Dakota Hope prepare to clash at UFC Fight Night: Moicano vs. Nolan, the dynamics of their matchup paint an intriguing picture. Marshall, standing at 5'9" with a reach of 72 inches, boasts a solid career record of 10-3, while the slightly more experienced Hope enters the octagon at 11-2. Looking at their striking styles, Hope comes in with a significant output, averaging 35.3 strikes per round compared to Marshall's 10.8. This disparity in striking volume could be pivotal, reminiscent of Brad Pickett's decisive win over Yves Jabouin in 2012, where the higher output ultimately overwhelmed his opponent.

However, don't count Marshall out just yet. His grappling game is where he truly shines, landing takedowns at a rate of 0.6 per round with an impressive accuracy of 41.7%. In contrast, Hope has attempted just 0.3 takedowns per round, which may leave him vulnerable if the fight shifts to the ground. Marshall's 71.4% finish rate adds an extra layer of threat, while Hope's relatively low finish rate of 20% suggests that if he can't keep the fight standing, he may struggle to secure a victory. With Marshall in his peak career stage and Hope in decline, this matchup has all the makings of an exciting contest that could echo past bouts where fighters with contrasting styles met for a thrilling showdown.

#FrancisMarshall #DakotaHope #UFCFightNight #Featherweight #UFC #MMA

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Prediction IntelClick here to expand

Stats Model Prediction

🔒 Prediction locked in before the fight · Predicted Oct 24, 2026, 18:03 UTC

Model Breakdown
Francis Marshall Dakota Hope
Deep Learning Model α 26% weight 66.6% 33.4%
Deep Learning Model ξ 25% weight 47.7% 52.3%
Statistical Model δ 13% weight 60.2% 39.8%
Statistical Model β 21% weight 65.3% 34.7%
Statistical Model ε 15% weight 64.9% 35.1%
Ensemble 64.9% 35.1%
AI Reasoning (why the models picked this)

Francis Marshall is favored due to his advantages in absorbed significant strikes and reach, as well as Dakota Hope's lower Elo rating. The ensemble prediction favors Francis Marshall, with calibration and weighting producing this outcome despite a closer split among individual models.

  • Statistical Model β: Model β favors Francis Marshall, citing his advantages in age, absorbed significant strikes, and reach over Dakota Hope.
  • Statistical Model ε: Model ε favors Francis Marshall, highlighting his advantage in absorbed significant strikes and reach against Dakota Hope.

AI-generated from the model outputs above — wording may occasionally be imprecise.

Predicted Winner
Francis Marshall
64.9%
Confidence
* Model output, not betting advice. Bet responsibly.

*New fighters, prediction made with limited information

Predicted Duration
3rd Round at 1m15s (11m15s total)

Chance the Fight Is Still Going

56% Chance of Decision

The curve stays above 50% all the way to the final bell, which is why the call above is a decision.

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Fighter IntelClick here to expand

Tale of the Tape

Stat Francis Marshall Dakota Hope
Career Record 10-3 11-2
Height 5' 9" —
Weight 145 lbs. 145 lbs.
Reach 72" —
Stance Orthodox —
Age 27 29

Records are official career records, all promotions included.

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Matchup IntelClick here to expand

How Similar Fights Ended

17 historical bouts

Not enough similar fights on record to quote a rate for this profile.

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.

Fight Francis Marshall Dakota Hope
69% 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
Apr 11, 2015
UFC Fight Night: Gonzaga vs Cro Cop 2
Welterweight
Fight Performance
Strikes (Per Rnd)
5.7
Strike accuracy
37.8%
Takedowns (Per Rnd)
1
Takedown accuracy
27.3%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
200s
Pawel Pawlak Winner
Decision 3rd Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
10
Strike accuracy
50%
Takedowns (Per Rnd)
1
Takedown accuracy
75%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
62.3s
69% 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
Sep 29, 2012
UFC on FUEL TV: Struve vs Miocic
Bantamweight
Brad Pickett Winner
Finish 1st Rnd, 3m40s
Fight Performance
Strikes (Per Rnd)
14
Strike accuracy
29.2%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
2s
Fight Performance
Strikes (Per Rnd)
26
Strike accuracy
45.6%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
0s
66% 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
Jun 28, 2014
UFC Fight Night: Te Huna vs Marquardt
Light Heavyweight
Gian Villante Winner
Decision 3rd Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
31
Strike accuracy
56.7%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
2.3s
Fight Performance
Strikes (Per Rnd)
36.3
Strike accuracy
47.8%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0.7
Control time (Per Rnd)
83.7s
64% 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
Mar 14, 2026
UFC Fight Night: Emmett vs. Vallejos
Featherweight
Fight Performance
Strikes (Per Rnd)
20.7
Strike accuracy
44%
Takedowns (Per Rnd)
1.3
Takedown accuracy
66.7%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
19.7s
Jose Delgado Winner
Decision 3rd Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
31.3
Strike accuracy
55.6%
Takedowns (Per Rnd)
0.3
Takedown accuracy
33.3%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
12s
63% 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
May 31, 2014
UFC Fight Night: Munoz vs Mousasi
Middleweight
Gegard Mousasi Winner
Finish 1st Rnd, 3m57s
Fight Performance
Strikes (Per Rnd)
18
Strike accuracy
62.1%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
2
Control time (Per Rnd)
92s
Fight Performance
Strikes (Per Rnd)
3
Strike accuracy
33.3%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
13s
62% 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
Dec 7, 2019
UFC Fight Night: Overeem vs. Rozenstruik
Women's Bantamweight
Aspen Ladd Winner
Finish 3rd Rnd, 0m33s
Fight Performance
Strikes (Per Rnd)
15.7
Strike accuracy
55.3%
Takedowns (Per Rnd)
0.7
Takedown accuracy
66.7%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
82.7s
Fight Performance
Strikes (Per Rnd)
15.7
Strike accuracy
58%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
77s
59% 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
Jan 15, 2017
UFC Fight Night: Rodriguez vs. Penn
Light Heavyweight
Finish 3rd Rnd, 2m05s
Fight Performance
Strikes (Per Rnd)
13.7
Strike accuracy
43.2%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
110.7s
Fight Performance
Strikes (Per Rnd)
7.3
Strike accuracy
40.7%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
22s
59% 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
Feb 22, 2015
UFC Fight Night: Bigfoot vs Mir
Featherweight
Mike de la Torre Winner
Finish 1st Rnd, 2m59s
Fight Performance
Strikes (Per Rnd)
16
Strike accuracy
53.3%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
31s
Fight Performance
Strikes (Per Rnd)
7
Strike accuracy
58.3%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
83s
58% 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
Jan 25, 2014
UFC on FOX: Henderson vs Thomson
Bantamweight
Fight Performance
Strikes (Per Rnd)
16.5
Strike accuracy
30.3%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
0s
Eddie Wineland Winner
Finish 2nd Rnd, 4m16s
Fight Performance
Strikes (Per Rnd)
27
Strike accuracy
39.1%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
37.5s
58% 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
May 29, 2010
UFC 114: Rampage vs Evans
Lightweight
Efrain Escudero Winner
Decision 3rd Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
21.3
Strike accuracy
34.8%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
31s
Fight Performance
Strikes (Per Rnd)
5.7
Strike accuracy
23.3%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
15s
58% 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
Mar 31, 2010
UFC Fight Night: Florian vs Gomi
Middleweight
Fight Performance
Strikes (Per Rnd)
4
Strike accuracy
18.2%
Takedowns (Per Rnd)
0
Takedown accuracy
0%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
0s
Yushin Okami Winner
Finish 2nd Rnd, 2m47s
Fight Performance
Strikes (Per Rnd)
25
Strike accuracy
69.4%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
75.5s
56% 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
Nov 18, 2006
UFC 65: Bad Intentions
Heavyweight
Fight Performance
Strikes (Per Rnd)
2.4
Strike accuracy
24%
Takedowns (Per Rnd)
0.2
Takedown accuracy
7.7%
Sub attempts (Per Rnd)
0.4
Control time (Per Rnd)
61.6s
Tim Sylvia Winner
Decision 5th Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
9.8
Strike accuracy
28%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0.2
Control time (Per Rnd)
69.4s
56% 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
Feb 6, 2021
UFC Fight Night: Overeem vs. Volkov
Featherweight
Ode Osbourne Winner
Finish 1st Rnd, 0m26s
Fight Performance
Strikes (Per Rnd)
5
Strike accuracy
83.3%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
2s
Fight Performance
Strikes (Per Rnd)
2
Strike accuracy
66.7%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
0s
56% 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
Jun 13, 2009
UFC 99: The Comeback
Lightweight
Fight Performance
Strikes (Per Rnd)
5
Strike accuracy
31.3%
Takedowns (Per Rnd)
1
Takedown accuracy
100%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
29s
Dennis Siver Winner
Finish 1st Rnd, 3m23s
Fight Performance
Strikes (Per Rnd)
8
Strike accuracy
34.8%
Takedowns (Per Rnd)
0
Takedown accuracy
—
Sub attempts (Per Rnd)
2
Control time (Per Rnd)
70s
56% 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
Apr 4, 2015
UFC Fight Night: Mendes vs Lamas
Lightweight
Fight Performance
Strikes (Per Rnd)
7
Strike accuracy
38.2%
Takedowns (Per Rnd)
0.7
Takedown accuracy
11.8%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
58s
Alexander Yakovlev Winner
Decision 3rd Rnd, 5m00s
Fight Performance
Strikes (Per Rnd)
10.3
Strike accuracy
43.1%
Takedowns (Per Rnd)
0.7
Takedown accuracy
40%
Sub attempts (Per Rnd)
0
Control time (Per Rnd)
57.7s

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Statistics IntelClick here to expand

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 Francis Marshall Dakota Hope UFC AVG
Per Round Average
Strikes 10.8 35.3 13.2
Strike accuracy 29.3% 41.1% 43.9%
Takedowns 0.6 0.3 0.4
Takedown accuracy 41.7% 33.3% 33.0%
Sub attempts 0.2 0 0.2
Control time 87.9s 26s 48.9s
Knockdowns 0.13 0.33 0.08
Knockdowns absorbed 0 0 0.13
Advanced Fighter Statistics
win rate Wins divided by this fighter's total recorded fights. 82.4% 71.4% 45.8%
recent win rate Win rate over the last 5 recorded fights only — a form signal, not a career figure. 60.0% 60.0% 37.6%
win streak Current run: a positive number is consecutive wins, a negative number consecutive losses. 2 -1 -2
total fights Total recorded fights, including bouts outside the UFC. 17 7 —
head strike share Share of this fighter's landed significant strikes that went to the head. Head, body and leg sum to 100%. 82.0% 58.5% —
body strike share Share of this fighter's landed significant strikes that went to the body. Head, body and leg sum to 100%. 7.0% 40.6% —
leg strike share Share of this fighter's landed significant strikes that went to the legs. Head, body and leg sum to 100%. 11.0% 0.9% —
sig strikes absorbed Significant strikes opponents land on this fighter PER ROUND, counted from the round-by-round UFC stats across their scored rounds. Lower is better. 14.44 35 15.2
takedowns absorbed Takedowns opponents complete on this fighter PER ROUND, counted from the round-by-round UFC stats across their scored rounds. Lower is better. 0.06 0 0.4
cardio sig ratio This 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. 1.21 — 0.52
cardio defence ratio What 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. 0.75 — 0.56
cardio takedown ratio This 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. 0.75 — 0.42
is orthodox Whether the fighter's recorded stance is orthodox. Yes No —
is southpaw Whether the fighter's recorded stance is southpaw. No No —
switch stance Whether the fighter is recorded as switching stance. No No —
finish rate Share of this fighter's WINS that came by finish, KO/TKO or submission. The denominator is wins, not fights. 71.4% 20.0% 46.5%
KO win rate Share of this fighter's WINS that came by KO or TKO. The denominator is wins, not fights. 21.4% 20.0% 27.9%
sub win rate Share of this fighter's WINS that came by submission. The denominator is wins, not fights. 50.0% 0.0% 18.7%
been stopped rate Share 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% 0.0% 52.3%
distance strike share Share of this fighter's landed significant strikes thrown at distance. Distance, clinch and ground sum to 100%. 89.0% 57.5% —
clinch strike share Share of this fighter's landed significant strikes thrown in the clinch. Distance, clinch and ground sum to 100%. 5.2% 41.5% —
ground strike share Share of this fighter's landed significant strikes thrown on the ground. Distance, clinch and ground sum to 100%. 5.8% 0.9% —
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. 10:30 15:00 —
Elo rating A UFC-only Elo rating: it rises and falls with results, weighted by the opponent's rating. 1500 is the starting and dataset-average value. 1,515.1 1,483.1 1500
PageRank How 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. 0.101 0.032 0.069
career stage Form 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. Peak Decline —
Market IntelClick here to expand

Betting Edge

Fighter Win confidence DraftKings odds Break-even Edge
Francis Marshall 64.9% 1.39 71.9% -9.9%
Dakota Hope 35.1% 3.10 32.3% +9.0%

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 stake No bet recommended at the price we recorded.

Market Odds

Sportsbook Francis Marshall Dakota Hope
US Decimal US Decimal
DraftKings -256 1.39 +210 3.10
FanDuel -294 1.34 +215 3.15
BetOnline -238 1.42 +200 3.00

Odds captured Oct 24, 2026, 6:02 PM

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