Next event · Sun, Nov 15

Polymarket UFC 334: Gane vs Hokit

Model win probabilities set against the best sportsbook prices — value picks only where the price pays more than the model says the fight is worth.

Odds
pulled Nov 13, 16:29 UTC
Model run
Nov 13, 17:55 UTC · feature-v1, trained Jul 20
Odds refresh once a day, around 16:00 UTC — not a live feed, so prices may have moved.
Title fight · main eventHeavyweight Title · 5 rounds
Ciryl Gane14-2
61%
Model favorite
Fair odds
-159
Best price
-190
Book
Bovada
VS
Josh Hokit#4 · 10-0
39%
Model
Fair odds
+159
Best price
+180
Book
DraftKings
Model win probability
61%39%

The model favors Ciryl Gane. Versus the market that is −2 pts on Ciryl Gane. Not +EV: −6.4% per unit at the best price, which needs 66% to break even.

Best Available Lines

Main event · best price across 6 sportsbooks, as of the last pull

Ciryl Gane to win
Bovada
-190
Josh Hokit to win
DraftKings
+180
Over 3.5 rounds
BetOnline.ag
+135
Under 3.5 rounds
BetOnline.ag
-155

Polymarket UFC 334: Gane vs Hokit

Sun, Nov 15

13 of 13 fights
Main Card
Heavyweight Title BoutTitle
Model
61%39%
Market (vig removed)6 books
64%36%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureGaneHokit
Model61%fav39%
Model fair odds-159+159
Best price-190Bovada+180DraftKings
Edge vs market−2 pts+2 pts
Expected value−6.4%+8.3%

Model favorite: Ciryl Gane. Not +EV: −6.4% per unit at the best price, which needs 66% to break even.

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 3.5 RoundsOver +135 / Under -155
Women's Bantamweight Title BoutTitle+EV value pick
Model
36%64%
Market (vig removed)6 books
61%39%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureHarrisonNunes
Model36%64%fav
Model fair odds+176-176
Best price-166BetOnline.ag+150BetMGM
Edge vs market−25 pts+25 pts
Expected value−42.0%+59.5%value pick

Model favorite: Amanda Nunes. Value pick: +59.5% expected return per unit at the best price.

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 3.5 RoundsOver +105 / Under -125
Middleweight Bout+EV value pick
Model
64%36%
Market (vig removed)6 books
59%41%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureBorralhoBelgaroui
Model64%fav36%
Model fair odds-177+177
Best price-158FanDuel+138BetOnline.ag
Edge vs market+5 pts−5 pts
Expected value+4.4%value pick−14.2%

Model favorite: Caio Borralho. Value pick: +4.4% expected return per unit at the best price.

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 2.5 RoundsOver -220 / Under +186
Welterweight Bout
Model
50%50%
Market (vig removed)5 books
59%41%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureMedicHolland
Model50%fav50%
Model fair odds-100+100
Best price-155DraftKings+149BetOnline.ag
Edge vs market−9 pts+9 pts
Expected value−17.6%+24.3%

Model favorite: Uros Medic. Below the 60% model-confidence bar for a value pick (−17.6% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 1.5 RoundsOver +125 / Under -145
Flyweight Bout
Model
57%43%
Market (vig removed)6 books
88%12%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureHasanGurule
Model57%fav⚠ Limited data43%
Model fair odds-132+132
Best price-950DraftKings+725BetMGM
Edge vs market−31 pts+31 pts
Expected value−37.2%+256.0%

Model favorite: Bilal Hasan. Below the 60% model-confidence bar for a value pick (−37.2% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 1.5 RoundsOver +145 / Under -165
Prelims
Welterweight Bout
Model
52%48%
Market (vig removed)5 books
57%43%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureThompsonRadtke
Model52%fav48%
Model fair odds-107+107
Best price-140BetOnline.ag+128FanDuel
Edge vs market−6 pts+6 pts
Expected value−11.3%+10.1%

Model favorite: Stephen Thompson. Below the 60% model-confidence bar for a value pick (−11.3% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 2.5 RoundsOver -190 / Under +165
Lightweight Bout
Model
40%60%
Market (vig removed)6 books
38%62%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureDoberDuncan
Model40%60%fav
Model fair odds+147-147
Best price+166BetOnline.ag-176FanDuel
Edge vs market+3 pts−3 pts
Expected value+7.5%−6.6%

Model favorite: Chris Duncan. Below the 60% model-confidence bar for a value pick (−6.6% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 1.5 RoundsOver -125 / Under +105
Lightweight Bout
Model
31%69%
Market (vig removed)6 books
35%65%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureMillerMcKinney
Model31%69%fav
Model fair odds+219-219
Best price+180FanDuel-205DraftKings
Edge vs market−3 pts+3 pts
Expected value−12.1%+2.1%

Model favorite: Terrance McKinney. Best price is shorter than -200, so there is little room for the market to be wrong (+2.1%).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 1.5 RoundsOver +290 / Under -350
Middleweight Bout+EV value pick
Model
66%34%
Market (vig removed)6 books
62%38%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureJohnsonAlmeida
Model66%fav34%
Model fair odds-196+196
Best price-170BetMGM+157BetOnline.ag
Edge vs market+5 pts−5 pts
Expected value+5.1%value pick−13.1%

Model favorite: Donte Johnson. Value pick: +5.1% expected return per unit at the best price.

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 1.5 RoundsOver -130 / Under +110
Early Prelims
Lightweight Bout
Model
30%70%
Market (vig removed)6 books
24%76%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureGordonCosta
Model30%70%fav
Model fair odds+229-229
Best price+315BetOnline.ag-380DraftKings
Edge vs market+7 pts−7 pts
Expected value+26.3%−12.1%

Model favorite: Melquizael Costa. Best price is shorter than -200, so there is little room for the market to be wrong (−12.1%).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 2.5 RoundsOver +115 / Under -135
Women's Bantamweight Bout
Model
49%51%
Market (vig removed)4 books
32%68%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureChiassonMesquita
Model49%51%fav
Model fair odds+106-106
Best price+205DraftKings-245FanDuel
Edge vs market+17 pts−17 pts
Expected value+48.4%−27.7%

Model favorite: Bia Mesquita. Below the 60% model-confidence bar for a value pick (−27.7% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 2.5 RoundsOver +153 / Under -175
Bantamweight Bout
Model
47%53%

No sportsbook odds yet, so there's no market number to compare against.

Model probability, fair odds, best price, edge and expected value for each fighter
MeasureAlatengheiliDiaz
Model47%53%fav⚠ Limited data
Model fair odds+111-111
Best priceNo odds yetNo odds yet
Edge vs market——
Expected value——

Model favorite: Juan Diaz. No sportsbook odds yet, so expected value can't be calculated.

No sportsbook odds yet
Lightweight Bout
Model
53%47%
Market (vig removed)6 books
48%52%
Model probability, fair odds, best price, edge and expected value for each fighter
MeasureElderSanches
Model53%fav47%⚠ Limited data
Model fair odds-113+113
Best price+100BetMGM-115Bovada
Edge vs market+5 pts−5 pts
Expected value+6.3%−12.4%

Model favorite: Evan Elder. Below the 60% model-confidence bar for a value pick (+6.3% at the best price).

Odds as of Nov 13, 16:29 UTC (3h ago)
Total 2.5 RoundsOver -110 / Under -110

Model Accuracy

Predictions recorded before each card started, graded against the real result.

62%
Live Hit Rate
0.239
Brier Score

98 of 159 fights across 14 events. With that many fights the true hit rate could plausibly be anywhere from 54% to 69%. The separate historical backtest scored 61% on 1,297 older held-out fights. Full track record

Accuracy per card, most recent first
0%25%50%75%100%-13-12-11-10-9-8-7-6-5-4-3-2-1This week
See every past card →

Why trust the model

No black box — here's what's actually under the hood.

Read the full methodology →
Elo, not vibes

Every fighter carries a rating built from real results, updated after every card.

Rigorously backtested

61% in a backtest on 1,297 older fights it never saw in training. Live results are tracked separately.

Market-aware, not market-copying

We price fights independently, then compare to the books — the gap is the whole point.