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Today · Oct 30 · 10 eventsLatest results· Oct 29
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Bout 8 of 12

Julian Erosa vs JeongYeong Lee

Sat, Oct 31, 5:00 PM ET · Featherweight · 3 rounds · UFC Fight Night: Moicano vs. Nolan · Meta APEX

Fight history: Julian Erosa · JeongYeong Lee

Simulation story

6 chapters · read from the published artifact
Skip to the report ↓
› Loading the matchup model› Reading the outcome distribution› Preparing the score scenariosPress Play to step through what the model expects, chapter by chapter, or read the report below.

Julian Erosa vs JeongYeong Lee

Featherweight, 3 rounds on UFC Fight Night: Moicano vs. Nolan. The model read both fighters' histories.

model ufc-fight-model@e657fc40b64dno run count recordedproduced Oct 29, 1:10 PM ET
Winner

Who the model expects to win

Probabilities over the two fighters, from the head that was evaluated on its own preregistered bar.

Julian ErosaJulian Erosa31-14-0
vs
JeongYeong LeeJeongYeong Lee11-3-0
Model pickJeongYeong Lee · 56.9%Decision 46.1% · Ends in round 3 or later 54.5%
31-14-0Record11-3-0
18Tracked bouts4
43.1%Win chance56.9%

From the tracked records (a summary, not the model's reasoning): JeongYeong Lee has the shorter tracked record (4 bouts to Erosa's 18). The model's method read has a decision as the most likely of three endings (46%), short of a majority.

Method

How it ends

Read among fights that end with a winner — a draw or no-contest sits outside this sample, so the three add to 100%.

KO / TKO26.7%
Submission27.3%
Decision46.1%
Round

How far it goes

R3+ carries every fight that reaches the judges as well as every round-3-or-later finish.

29
R1
17
R2
55
R3+
Ends in round 1
28.8%
Ends in round 2
16.6%
Ends in round 3 or later
54.5%
Goes the distance
46.1%

“Goes the distance” is the method head’s decision probability, not a separate model — so it cannot disagree with the bar above it.

The fighters

What the corpus knows about each of them

Tracked bouts only — a fight outside the corpus is not counted, and a thin record says so.

Julian Erosa
31-14-0
Tracked record

3-2 in the last 5 tracked bouts. 6 of 9 wins came by finish (67%); 5 of 18 tracked fights reached the judges (28%).

Tendencies
· Most wins come inside the distance — 6 of 9, mostly by submission (2 KO/TKO, 4 submission)
· Most losses come inside the distance — 7 of 9 (7 KO/TKO, 0 submission)
Not established
? Neither a strength nor a weakness: 50% win rate across 18 tracked bouts (9-9)
Last 5 tracked
LLerryan DouglasKO / TKO R1
LMelquizael CostaDecision R3
WDarren ElkinsKO / TKO R1
WChristian RodriguezSubmission R1
WRicardo RamosSubmission R1
JeongYeong Lee
11-3-0
Tracked record

2-2 in the last 4 tracked bouts. 0 of 2 wins came by finish (0%); 3 of 4 tracked fights reached the judges (75%).

Not established
? Only 4 tracked bouts — too few to call a strength or weakness (needs 5)
? Only 2 tracked losses — too few to say how fights are lost; absence of data, not absence of weakness
Last 4 tracked
LDaniel SantosDecision R3
LHyder AmilKO / TKO R1
WBlake BilderDecision R3
WYizhaDecision R3
Method

Where these numbers come from

Three separate heads — winner, method and round — each fitted on a corpus of tracked UFC fights and each tested on past fights it never trained on before it was published. This is an experimental model: winner forecasts are graded on every new card, method and round are not yet graded, and it has not been shown to have an edge over the market.

Winner 60.6% accurate over 3,557 held-out fights · baseline 50.0% · log loss 0.6615 against 0.6931
Method 52.7% accurate over 3,557 held-out fights · baseline 46.7% · log loss 0.9692 against 1.0255
Round 60.6% accurate over 3,557 held-out fights · baseline 55.3% · log loss 0.9148 against 0.9549

Generated

Technical detailsModel fingerprint and the fight corpus it was fitted on.
model ufc-fight-model@e657fc40b64d
corpus 8,642 fights · 1994-03-11 to 2026-08-08 · scrape_ufc_stats (GPL-3.0)

Educational and paper-only — not betting advice.

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