Daejeon Citizen games went over 2.5 goals in 9 of their last 10 (league 46%).
K-League 1 Predictions & Stats
Free AI predictions for every upcoming K-League 1 match — 1X2, Both Teams to Score, Over/Under goals and Correct Score probabilities.
Predictions updated on 30 October 2026.
K-League 1 Predictions by Market
Season 2026 · Round 34 · Championship Round
Full-Time Result
41%
SUCCESS RATE AVG.
Both Teams To Score
52%
SUCCESS RATE AVG.
Over/Under 2.5 Goals
46%
SUCCESS RATE AVG.
Over/Under 3.5 Goals
69%
SUCCESS RATE AVG.
First Half Result
54%
SUCCESS RATE AVG.
Correct Score
12%
SUCCESS RATE AVG.
K-League 1 2026 prediction accuracy over the last 100 matches: 1X2 41%, BTTS 52%, Over/Under 2.5 46%, Over/Under 3.5 69%, correct score 12%.
K-League 1 stats: goals, BTTS, corners and cards vs other leagues
How this competition ranks among the leagues and cups we cover for goals, chances (xG), corners and cards.
How to read it
last 12 months · 222 matchesrank 1 = highest of 63 competitionsTight and cageyAway days payDraws aplenty
Goals a match
2.45
53rd of 63
xG a match
2.53
53rd of 62
Corners a match
Cards a match
Calculated by MyGameOdds · xG: our own model
How it works
We use the league's matches from the last 12 months, without qualifying rounds, and rank it against the 63 leagues and club competitions with 50 or more matches in that time (1 = highest). A label marks a league in the top fifth on goals, home or away wins, draws, cards or corners, or in the bottom fifth on goals. xG is our estimate of each match's chances from its shots.
K-League 1: the stats that stand out
The K-League 1 teams most unusual in their last 10 games.
How to read it
the teamleague averageeach team's last 10 gamesCalculated by MyGameOdds
How it works
For each stat we show the club that stands out most, one club per stat. A fact needs at least 6 games and a result far enough from the league average to be unusual (at least one standard deviation).
How we measure →Today's Betting Tips for K-League 1 South Korea
Free predictions for today's K-League 1 matches: 1X2, both teams to score, over/under and correct score.
Winner
12 71%
BTTS*
Yes 58%
Correct Score
1-1 13%
Over/Under 2.5 goals
over 53%
Over/Under 3.5 goals
under 59%
Winner
12 71%
BTTS*
Yes 58%
Correct Score
1-1 13%
Over/Under 2.5 goals
over 53%
Over/Under 3.5 goals
under 59%
Full Time
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 26% | 74% | 60% | 40% | |
| 28% | 72% | 62% | 38% |
Goals Over/Under
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| FT | 47% | 53% | 59% | 41% |
Correct Score
1-1
13.0%
2-1
9.1%
1-2
8.5%
1-0
8.4%
0-1
8.1%
0-0
6.9%
2-2
6.8%
Winner
2 54%
BTTS*
Yes 52%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 52%
Over/Under 3.5 goals
under 60%
Winner
2 54%
BTTS*
Yes 52%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 52%
Over/Under 3.5 goals
under 60%
Winner
1X 69%
BTTS*
Yes 52%
Correct Score
1-1 14%
Over/Under 2.5 goals
under 56%
Over/Under 3.5 goals
under 67%
Winner
1X 69%
BTTS*
Yes 52%
Correct Score
1-1 14%
Over/Under 2.5 goals
under 56%
Over/Under 3.5 goals
under 67%
Winner
1X 71%
BTTS*
Yes 55%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 51%
Over/Under 3.5 goals
under 64%
Winner
1X 71%
BTTS*
Yes 55%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 51%
Over/Under 3.5 goals
under 64%
Winner
1X 76%
BTTS*
Yes 50%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 54%
Over/Under 3.5 goals
under 66%
Winner
1X 76%
BTTS*
Yes 50%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 54%
Over/Under 3.5 goals
under 66%
Winner
12 71%
BTTS*
Yes 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 56%
Over/Under 3.5 goals
under 68%
Winner
12 71%
BTTS*
Yes 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 56%
Over/Under 3.5 goals
under 68%
Winner
1X 75%
BTTS*
Yes 57%
Correct Score
1-1 13%
Over/Under 2.5 goals
over 54%
Over/Under 3.5 goals
under 59%
Winner
1X 75%
BTTS*
Yes 57%
Correct Score
1-1 13%
Over/Under 2.5 goals
over 54%
Over/Under 3.5 goals
under 59%
Winner
12 73%
BTTS*
Yes 54%
Correct Score
1-1 12%
Over/Under 2.5 goals
over 51%
Over/Under 3.5 goals
under 62%
Winner
12 73%
BTTS*
Yes 54%
Correct Score
1-1 12%
Over/Under 2.5 goals
over 51%
Over/Under 3.5 goals
under 62%
Winner
1X 72%
BTTS*
Yes 54%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 51%
Over/Under 3.5 goals
under 64%
Winner
1X 72%
BTTS*
Yes 54%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 51%
Over/Under 3.5 goals
under 64%
Winner
1X 73%
BTTS*
Yes 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 53%
Over/Under 3.5 goals
under 65%
Winner
1X 73%
BTTS*
Yes 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 53%
Over/Under 3.5 goals
under 65%
Winner
12 73%
BTTS*
Yes 52%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 54%
Over/Under 3.5 goals
under 66%
Winner
12 73%
BTTS*
Yes 52%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 54%
Over/Under 3.5 goals
under 66%
Winner
1X 71%
BTTS*
No 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 55%
Over/Under 3.5 goals
under 67%
Winner
1X 71%
BTTS*
No 51%
Correct Score
1-1 13%
Over/Under 2.5 goals
under 55%
Over/Under 3.5 goals
under 67%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
K-League 1 xG: chances created and allowed
Every K-League 1 team's chances created and allowed a game, measured with our own xG.
How to read it
each logo is a team · tap one for detailseach logo is a team · hover one for detailsK-League 1 average · 1.31 xG, 1.31 xGAlast 10 games each↑ Fewer chances allowed (xGA a game)












More chances created (xG a game) →
Teams by box· 12
Calculated by MyGameOdds · xG: our own model
How it works
xG is our estimate of how many goals a team's chances were worth, from the shots in each match; xGA is the same for the chances it allowed. The dashed lines are the average of the teams shown. A team close to a line is about average. Teams with fewer than 5 games here aren't in the chart yet.
How we measure →K-League 1 Results vs the Odds
Season 2026 and the last 30 days
How often each result has happened in K-League 1 this season (thick bar) and in the last 30 days (thin bar), next to what the bookmakers’ closing odds expected. The last 30 days cover fewer matches, so their normal range is wider and big swings there are still normal. This is not our prediction accuracy.
How to read it
Home wins
198 matches
31.8%
Draws
198 matches
33.8%
Away wins
198 matches
34.3%
Over 2.5 goals
198 matches
47.0%
Both teams scored
198 matches
54.5%
Show more markets (6)Show fewer markets
Over 3.5 goals
198 matches
24.7%
Home side ahead at half-time
198 matches
18.7%
Level at half-time
198 matches
51.5%
Away side ahead at half-time
198 matches
29.8%
Home team scored 2+
198 matches
34.8%
Away team scored 2+
198 matches
35.9%
Outside the normal range this season: Home wins 31.8% vs 39.4% expected (chance alone: about 1 in 45); Draws 33.8% vs 27.5% expected (chance alone: about 1 in 25); Home side ahead at half-time 18.7% vs 30.3% expected (chance alone: 1 in 1,000 or less); Level at half-time 51.5% vs 44.0% expected (chance alone: about 1 in 30).
Shows what happened, not what comes next. Closing odds from one bookmaker per match, bookmaker margin removed. Updated daily.
Show as a tableHide the table
| Result | Period | Matches | Happened | Odds expected | Gap (pts) | Normal range (± pts) | Verdict |
|---|---|---|---|---|---|---|---|
| Home wins | Season | 198 | 31.8% | 39.4% | −7.6 | ±6.5 | Fewer than expected |
| Home wins | 30 days | 18 | 50.0% | 45.3% | +4.7 | ±22.1 | Normal range |
| Draws | Season | 198 | 33.8% | 27.5% | +6.4 | ±6.2 | More than expected |
| Draws | 30 days | 18 | 33.3% | 25.7% | +7.6 | ±20.1 | Normal range |
| Away wins | Season | 198 | 34.3% | 33.1% | +1.2 | ±6.3 | Normal range |
| Away wins | 30 days | 18 | 16.7% | 29.0% | −12.3 | ±20.1 | Normal range |
| Over 2.5 goals | Season | 198 | 47.0% | 45.4% | +1.6 | ±6.9 | Normal range |
| Over 2.5 goals | 30 days | 18 | 66.7% | 51.4% | +15.3 | ±22.8 | Normal range |
| Both teams scored | Season | 198 | 54.5% | 49.4% | +5.1 | ±6.9 | Normal range |
| Both teams scored | 30 days | 18 | 72.2% | 52.6% | +19.6 | ±23.0 | Normal range |
| Over 3.5 goals | Season | 198 | 24.7% | 24.2% | +0.6 | ±5.9 | Normal range |
| Over 3.5 goals | 30 days | 18 | 33.3% | 29.7% | +3.6 | ±20.9 | Normal range |
| Home side ahead at half-time | Season | 198 | 18.7% | 30.3% | −11.6 | ±6.3 | Fewer than expected |
| Home side ahead at half-time | 30 days | 18 | 11.1% | 35.1% | −24.0 | ±21.6 | Fewer than expected |
| Level at half-time | Season | 198 | 51.5% | 44.0% | +7.5 | ±6.9 | More than expected |
| Level at half-time | 30 days | 18 | 55.6% | 41.5% | +14.0 | ±22.7 | Normal range |
| Away side ahead at half-time | Season | 198 | 29.8% | 25.8% | +4.0 | ±6.0 | Normal range |
| Away side ahead at half-time | 30 days | 18 | 33.3% | 23.4% | +9.9 | ±19.2 | Normal range |
| Home team scored 2+ | Season | 198 | 34.8% | 37.7% | −2.9 | ±6.6 | Normal range |
| Home team scored 2+ | 30 days | 18 | 61.1% | 45.8% | +15.3 | ±22.4 | Normal range |
| Away team scored 2+ | Season | 198 | 35.9% | 32.4% | +3.5 | ±6.4 | Normal range |
| Away team scored 2+ | 30 days | 18 | 38.9% | 31.5% | +7.4 | ±20.9 | Normal range |
K-League 1 luck check: the last 10 games
K-League 1 teams taking more or fewer points than their chances usually bring, measured with our own xG.
How to read it
what their chances usually bringnormal range (±4)outside it+4.5 = 5 points more than their chances usually bringRiding their luck1
Daejeon CitizenClinical · +8 goals+4.5
Unlucky2
Sangju SangmuWasteful · −3 goals−4.4
Gangwon9 of 10 games−4.2
Points in line, but clinical: Gwangju (+4 goals, 9 games).
In line with their chances: Ulsan, Anyang, Jeju United, Pohang Steelers, Jeonbuk Motors, Incheon United, Seoul and Bucheon 1995.
Calculated by MyGameOdds · xG: our own model
How it works
For each of a team's last 10 games, we work out how many points a team usually gets from a game with those chances (xG) for and against, add them up and compare with the points it actually got. We do the same for goals. Strong teams often get a bit more than their chances suggest, so we compare each team with sides of similar strength in this league. That way nobody is flagged just for being good.
We flag a team when the gap is 4 points or more (or 3 goals or more). If some games have no xG data, we use the ones that do.
Does it mean anything? 85% of teams 4+ points ahead of their chances got fewer points in their next 10 games, and 83% of teams 4+ points behind got more. Bookmakers already expect these gaps to even out, so it's a fan's read, not a betting edge.
How we measure →K-League 1 last week: smash-and-grab wins and upsets
Smash-and-grab wins (the side with clearly fewer chances won) and upsets (results the closing odds gave under 20%) from the last 7 days.
How to read it
Oct 23–Oct 30 · 6 matches · odds: closing, margin removedNo smash-and-grab wins or upsets in these 6 matches.
Calculated by MyGameOdds · xG: our own model
How it works
Smash-and-grab: the winner had at least 0.8 less xG than the loser (our xG, from shots). Upset: the result the closing odds gave under 20%, with the bookmaker margin removed. Across our leagues about 6% of matches are smash-and-grab wins and about 5% are upsets.
How we measure →K-League 1 Standings
Check the current league table, team positions, points, and form. Click to view complete standings with detailed statistics.
#TEAM | MP | PTS | W | D | L | G | GD | FORM |
|---|---|---|---|---|---|---|---|---|
1 | 33 | 67 | 20 | 7 | 6 | 61:29 | +32 | D D W L W |
2 | 33 | 51 | 15 | 6 | 12 | 52:47 | +5 | D W L L W |
3 | 33 | 49 | 13 | 10 | 10 | 53:41 | +12 | W W W D D |
4 | 33 | 48 | 12 | 12 | 9 | 43:33 | +10 | D W L D L |
5 | 33 | 48 | 11 | 15 | 7 | 40:30 | +10 | D D W D L |
The league profile compares K-League 1 with the 63 leagues and cups we rank over the last 12 months (rank 1 = highest). The stats that stand out pick the most unusual numbers from each team's last 10 games. The attack vs defence chart puts each team in one of four boxes: top right creates more and allows fewer chances than the league average. The luck check shows who got more or fewer points than their chances in the last 10 games, and Last week lists wins with fewer chances and results the bookmakers gave under 20%.
These statistics represent prediction accuracy based on the last 100 matches in the league. Accuracy reflects how often the model correctly predicted the outcome for each market. Our football predictions are generated using advanced AI techniques combined with historical match data, team form, player availability and head-to-head records to deliver reliable forecasts. Explore our prediction results tracker for live accuracy across all completed matches, our league accuracy data for competition-level breakdowns, or prediction performance for team-level insights.
About K-League 1
The K League 1 is the top professional football league in South Korea. It consists of 12 teams and operates on a system of promotion and relegation. The K League 1 is known for its technical quality and disciplined play. Jeonbuk Hyundai Motors and FC Seoul are the most successful clubs in K League 1 history.