Jagiellonia 1-0 Wisla Plock: result, our prediction

Ekstraklasa
JagielloniaJagielloniaWLLLL
Full time1-0Sun, 25 Oct 202625/1013:45UK
Wisla PlockWisla PlockDWWLW
53.9%Home winFair odds 1.86
25.8%DrawFair odds 3.88
20.3%Away winFair odds 4.93
Pre-match: Joint most likely published scores1-0 / 1-112.3%Fair odds 8.16

Pre-match model estimates · MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Jagiellonia or draw79.7%
Under 3.5 goalsBoth teams combined74.8%
Over 1.5 goalsBoth teams combined72.7%

Prediction snapshot · Model generated .

Post-match analysis

Judged against the prediction this page published before kickoff. Right or wrong, it stays on the record.

A call is the side our published probability favoured. If we leaned towards under and three goals went in, that counts as a miss.

The half-by-half shots come from a different source than the match shot total, and we only use them when the shots before the break add up to the actual half-time score. That is why the two numbers can differ slightly.

JagielloniaJagiellonia
1-0FT
Wisla PlockWisla Plock

Match data

Match data: Jagiellonia and Wisla Plock
JagielloniaJagiellonia Statistic Wisla PlockWisla Plock
1 Goals 0
0 Goals, 1st half 0
1 Goals, 2nd half 0
21 Shots 7
8 Shots, 1st half 2
13 Shots, 2nd half 5
4 Shots on target 4
2 On target, 1st half 2
2 On target, 2nd half 2
8 Corners 3
0 Yellow cards 0
0 Red cards 0
16 Fouls 12

RefereeDamian Kos

The result, on the record

Recorded tally 4 of 5 published calls on this match were right.

Published calls · recorded grading

# Market Our pick Our chance Recorded grade
1 Match result Pick: Jagiellonia Chance: 53.9% Correct
2 Total goals 2.5 Pick: Under 2.5 Chance: 53.3% Correct1 goals
3 Total goals 1.5 Pick: Over 1.5 Chance: 72.7% Wrong1 goals
4 Total goals 3.5 Pick: Under 3.5 Chance: 74.8% Correct1 goals
5 Both teams to score Pick: No Chance: 51.4% Correct

Our verdict

Road2Sushi's own call on this match: the likeliest result, how confident the model is, its strongest signals and the reasons behind them.

Every percentage is a model estimate and every fair price is 1 divided by that estimate. Neither is a bookmaker offer, and a model call is not a proven edge over the market.

Model pick

Jagiellonia
Match winner (1X2)53.9%
Fair odds1.86
Save model pickSaved to my bets

Top signals

Double chance marketJagiellonia or draw
Model estimateModel79.7%
Fair oddsFair1.25
Goals marketUnder 3.5 goals
Model estimateModel74.8%
Fair oddsFair1.34
Both teams to scoreNot both teams to score
Model estimateModel51.4%
Fair oddsFair1.95

Model read

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. Jagiellonia lead the result estRead full analysisShow less

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. Jagiellonia lead the result estimates at 53.9%. The match still has meaningful room for a draw or an opponent win. Jagiellonia win stands out at 53.9%. The estimate leans this way, with substantial uncertainty remaining. Without a complete matching price comparison, this is an event read rather than a verified price opportunity.

Jagiellonia win

Model estimate
53.9%
Fair odds
1.86

Under 2.5 goals

Model estimate
53.3%
Fair odds
1.88

Not both teams to score

Model estimate
51.4%
Fair odds
1.95

Context & limits

  • Jagiellonia: 1 wins, 0 draws and 4 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Wisla Plock: 3 wins, 1 draws and 1 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 2.6 goals. This is a historical sample, not a forecast for this fixture.
  • A complete matching price comparison is unavailable for this selection, so a price edge cannot be established.
Additional match context

Few Ekstraklasa fixtures are this lopsided in the data: Jagiellonia carry a 54% win probability against Wisla Plock on 25 October 2026. The numbers that frame it: • Totals sit close to the fence: 47% for Over 2.5 with both teams to score at 49%. • Head to head, the last 5 meetings gave 2 wins for Jagiellonia, 1 draws and 2 for Wisla Plock, averaging 2.6 goals a game. • Form guide over the last six: Jagiellonia W1 D0 L5, Wisla Plock W3 D1 L2. Discipline says sit it out: no bookmaker price published for this match yet.

Form & head-to-head

Recent form uses each club’s available results in their stored order. Select a W/D/L result for details.

Head-to-head figures use their own recorded sample. Where individual results are available, the figures and journal cover the same meetings. Missing results are never counted as draws.

JagielloniaJagielloniaLast 5
W
Win · 2-1
L
Loss · 0-2
L
Loss · 1-3
L
Loss · 1-3
L
Loss · 0-1

1 win · 0 draws · 4 losses

Wisla PlockWisla PlockLast 5
D
Draw · 1-1
W
Win · 3-1
W
Win · 2-0
L
Loss · 0-3
W
Win · 1-0

3 wins · 1 draw · 1 loss

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

2JagielloniaJagiellonia wins
1Draws
2Wisla PlockWisla Plock wins
2.6Average goals
Date
Home team
Score
Away team
JagielloniaJagiellonia
1 – 2
Wisla PlockWisla Plock
Wisla PlockWisla Plock
0 – 1
JagielloniaJagiellonia
Wisla PlockWisla Plock
2 – 4
JagielloniaJagiellonia
JagielloniaJagiellonia
1 – 1
Wisla PlockWisla Plock
JagielloniaJagiellonia
0 – 1
Wisla PlockWisla Plock

Odds: model vs bookmaker

Every price for this match in one place: the model's probabilities next to the bookmaker's, the bookmaker's prices with our gap, and the model's own fair odds for each market.

Bookmaker probabilities are de-vigged (the margin is removed) and come from one bookmaker. A gap between the model and that bookmaker is a disagreement, not a proven edge. Fair odds are 1 divided by the model probability, not a bookmaker quote.

Model vs market

Pre-match estimates, recorded before the match.

1X2, Goals and Corners: Bet365 prices via API-Football, observed 24 Oct 2026, 19:21 UTC, with the bookmaker margin taken out.

A market probability is the bookmaker's own price with its margin taken out, so the outcomes of each line add up to 100%. A gap from our model is a disagreement, not a proven edge: when we tested 1X2 and goal totals on matches the model had never seen, the bookmaker's closing price was more accurate. For corners, cards and shots we have no such test.

Every market price shown was recorded before kick-off.

1X2

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 53.9%
Jagiellonia

Model minus market: +6.2 pp
Market probability: 47.7%
Model probability: 25.8%
Draw

Model minus market: +1.1 pp
Market probability: 24.7%
Model probability: 20.3%
Wisla Plock

Model minus market: -7.3 pp
Market probability: 27.6%

Goals

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 91.6%
Over 0.5 goals

Model minus market: -3.6 pp
Market probability: 95.2%
Model probability: 8.4%
Under 0.5 goals

Model minus market: +3.7 pp
Market probability: 4.8%
Model probability: 72.7%
Over 1.5 goals

Model minus market: -7.4 pp
Market probability: 80.1%
Model probability: 27.3%
Under 1.5 goals

Model minus market: +7.4 pp
Market probability: 19.9%
Model probability: 46.7%
Over 2.5 goals

Model minus market: -9.9 pp
Market probability: 56.7%
Model probability: 53.3%
Under 2.5 goals

Model minus market: +9.9 pp
Market probability: 43.3%
Model probability: 25.2%
Over 3.5 goals

Model minus market: -9.2 pp
Market probability: 34.4%
Model probability: 74.8%
Under 3.5 goals

Model minus market: +9.2 pp
Market probability: 65.6%
Model probability: 11.5%
Over 4.5 goals

Model minus market: -5.8 pp
Market probability: 17.3%
Model probability: 88.5%
Under 4.5 goals

Model minus market: +5.8 pp
Market probability: 82.7%
Model probability: 4.5%
Over 5.5 goals

Model minus market: -3.3 pp
Market probability: 7.8%
Model probability: 95.5%
Under 5.5 goals

Model minus market: +3.3 pp
Market probability: 92.2%
Model probability: 48.6%
Both teams to score · Yes

Model minus market: -11.0 pp
Market probability: 59.6%
Model probability: 51.4%
Both teams to score · No

Model minus market: +11.0 pp
Market probability: 40.4%

Cards

No estimates available for this market.

Corners

No estimates available for this market.

Shots

No estimates available for this market.

Model fair odds

Our published model probability as a decimal price (1 divided by probability). A fair model price, not a bookmaker quote. Only the supported 1X2 calibration pool is calibrated; other markets retain their model estimates.

Match result

Jagiellonia win1.86
Draw3.88
Wisla Plock win4.93
Both teams to score2.06

Goals

Over 0.5 goals1.09
Over 1.5 goals1.37
Over 2.5 goals2.14
Over 3.5 goals3.97
Jagiellonia most1.86
Wisla Plock most4.92

Totals line guide

Both teams combined.

Over 0.591.6%Over 1.572.7%Over 2.546.7%Over 3.525.2%Over 4.511.5%Over 5.54.5%
Our stored model focusOver 1.572.7%

The stored model call was Our price. The match has been played, so this is a historical snapshot: the graded result is below.

Read context

Both teams combined. Each bar uses the stored model estimate for that exact total-goals line. Missing estimates are unavailable; they are not zero.

Fair odds are the model’s own probability price, not a published bookmaker offer.

Market explorer

Model probabilities and fair odds.

Each bar is a specific Over selection for both teams combined. Its height is the model probability, on the same 0–100% scale.

Risk describes estimated likelihood, not profitability: low risk at least 62%, medium 48% to under 62%, high below 48%. Colors follow the actual estimate, even when a risk band is missing.

Up to four markets are selected from available model data, prioritising a spread of risk profiles. Fair odds are calculated from the model, not bookmaker prices: 1 divided by probability.

Scores are exact home-away outcomes from zero to five goals per team. Unavailable estimates stay blank; partial inputs are not expanded, inferred or normalised. Scores outside the matrix remain eligible for the top three.

Low riskMedium riskHigh risk

Goals

Over 0.50.5 goals, Low risk
Model probability 91.6%
Fair odds Fair 1.09
Over 1.51.5 goals, Low risk
Model probability 72.7%
Fair odds Fair 1.37
Over 3.53.5 goals, High risk
Model probability 25.2%
Fair odds Fair 3.97
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-08.4%Fair odds 11.85 1-012.3%Fair odds 8.16 2-010.5%Fair odds 9.52 3-05.7%Fair odds 17.48 4-02.3%Fair odds 42.74 5-00.8%Fair odds 131.58
Away goals 1 0-16.6%Fair odds 15.24 1-112.3%Fair odds 8.16 2-19.5%Fair odds 10.48 3-15.2%Fair odds 19.23 4-12.1%Fair odds 47.17 5-10.7%Fair odds 144.93
Away goals 2 0-23.3%Fair odds 30.77 1-25.3%Fair odds 18.83 2-24.3%Fair odds 23.04 3-22.4%Fair odds 42.37 4-21.0%Fair odds 103.09 5-20.3%Fair odds 312.50
Away goals 3 0-31.0%Fair odds 102.04 1-31.6%Fair odds 62.11 2-31.3%Fair odds 76.34 3-30.7%Fair odds 138.89 4-30.3%Fair odds 344.83 5-30.1%Fair odds 1,000.00
Away goals 4 0-40.2%Fair odds 454.55 1-40.4%Fair odds 270.27 2-40.3%Fair odds 333.33 3-40.2%Fair odds 625.00 4-40.1%Fair odds 1,428.57 5-40.0%Fair odds 5,000.00
Away goals 5 0-50.0%Fair odds 2,500.00 1-50.1%Fair odds 1,428.57 2-50.1%Fair odds 2,000.00 3-50.0%Fair odds 3,333.33 4-50.0%Fair odds 10,000.00 5-50.0%Fair odds ·

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-0
Model probability12.3%
Fair odds8.16
1-1
Model probability12.3%
Fair odds8.16
2-0
Model probability10.5%
Fair odds9.52

Referee

One match referee is shown from an explicitly saved result or a fresh, identity-matched provider fixture. Previous referees are never used to guess an appointment. An API listing can change.

The referee’s totals count every completed match with this referee in our data: football-data.co.uk names the referee in English leagues, and API-Football names the referee of the same match (same teams, date and score) in every league from 2025/26. A rate needs at least 5 matches with that figure.

The team table shows each team’s published history with that same referee only. Matches, team cards per game and match cards per game are separate fields; their available samples can differ. Missing values are not zero. Cards include yellow and red cards in the current historical source.

Recorded match referee.

Damian Kos in our data
Per match All matches 2026/27
Matches 23 6
Goals 2.17 2.50
Yellow cards 4.86 4.33
Red cards Not available 0.00
Corners 10.7 9.5
Fouls 25.1 25.5
Both teams scored 39% 33%
Over 2.5 goals 30% 33%
Home wins 48% 33%
Latest 10 matches
Date Match Score Goals BTTS Yellow Red Corners Fouls
25 Oct 2026 Jagiellonia vs Wisla Plock 1-0 1 No 0 0 11 28
9 Oct 2026 Rakow vs GKS Katowice 1-4 5 Yes 5 0 10 24
15 Sep 2026 Korona Kielce vs Gornik Zabrze 0-2 2 No 3 0 9 17
6 Sep 2026 Lech Poznan vs Rakow 1-0 1 No 6 0 10 25
23 Aug 2026 Pogon Szczecin vs Wisla 2-2 4 Yes 5 0 6 27
9 Aug 2026 Jagiellonia vs Widzew Lodz 0-2 2 No 7 0 11 32
24 Apr 2026 Zaglebie vs Termalica B-B. 1-2 3 Yes 8 1 10 27
11 Apr 2026 Legia vs Gornik Zabrze 1-1 2 Yes 7 Not available 9 24
6 Apr 2026 Termalica B-B. vs Piast Gliwice 3-2 5 Yes 6 1 12 19
20 Mar 2026 Motor Lublin vs Zaglebie 1-0 1 No Not available Not available 9 27

Damian Kos referee stats

Team history with this referee
Team
Jagiellonia Not available Not available Not available
Wisla Plock Not available Not available Not available

No matching history for this referee is available for one or both teams.

Season stats

2026/27 season. Recorded results, not model estimates.

JagielloniaJagiellonia
Wisla PlockWisla Plock

Overview

Statistic
Jagiellonia
Wisla Plock
League position
#12 of 18
#10 of 18
Matches played
10
10
Record W-D-L
4-0-6
4-2-4
Recent form
WLLLL
Last 5 matches
DWWLW
Last 5 matches
Current streak
L4
W1
Points per game
1.20
1.40
Record, home vs away
2-0-3
2-1-3
PPG, home vs away
1.20
1.17

PPG scale: 0–3 points per game. Each team uses the same scale independently.

Show all season statsHide season stats

Goals

Statistic
Jagiellonia
Wisla Plock
Goals scored per game
1.30
1.00
Goals conceded per game
1.70
1.50
Scored, home vs away
1.00
1.00
Conceded, home vs away
1.80
2.00
1st half goals per game
0.88
0.44
2nd half goals per game
0.62
0.56

Scale: 0–3 goals or expected goals (xG) per game. Each team uses the same scale independently.

Goal rates

Statistic
Jagiellonia
Wisla Plock
Over 2.5 rate
60.0%
50.0%
BTTS rate
60.0%
40.0%
Clean sheets
10.0%
30.0%

Scale: 0–100% of recorded matches, not model estimates. Each team uses the same scale independently.

League averages this season: 2.99 goals per match · Over 2.5 in 59.8% · BTTS in 65.7%. Full league tables & stats →

First half / second half

Averages per game in this season’s league matches, split at half-time. Games is the number of each team’s matches with verified half data for that row; below five matches the row stays blank, and a missing value is never a zero.

Corners, shots on target and yellow cards per half come from the data provider’s half-by-half match statistics and are only used when the two halves add up to the full-time count. Cards are split by the minute they were shown, and first-half stoppage time counts as the first half. These are recorded results, not predictions.

In the Premier League, La Liga, Bundesliga, Serie A and Ligue 1 the shots per half come from a different source than the match shot totals, so the two can differ slightly.

This match

This match by half: Jagiellonia and Wisla Plock
Jagiellonia Wisla Plock
Statistic 1H 2H 1H 2H
Goals 0 1 0 0
Shots 8 13 2 5
Shots on target 2 2 2 2
Corners 3 5 2 1
Yellow cards 0 0 0 0
JagielloniaJagiellonia
Jagiellonia: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.88 0.62 8
Goals concededConceded 0.62 1.00 8
Wisla PlockWisla Plock
Wisla Plock: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.44 0.56 9
Goals concededConceded 0.67 1.00 9
All model outcomes · full market spectrum & player markets

Shots

Shots on target

Cards

Clean sheet & win to nil

Worked out from the scoreline grid above: a clean sheet is every scoreline where the other side fails to score. It is the model’s own percentage, scored against the result afterwards, and it is not a tip.

Jagiellonia clean sheet 40.0%
Wisla Plock clean sheet 19.5%
Jagiellonia win to nil 31.6%
Wisla Plock win to nil 11.1%

Full market spectrum · model probabilities

The model’s own percentages, with no odds attached. The smaller markets are here so you can see everything we hold a number on, not because we claim an advantage in them. The colour says how close our percentages have landed to reality on matches the model had never seen. This is the raw model spectrum. Its match-result marginal can differ from the published 1X2 above; it does not replace the saved prediction.

Match result & goals calibrated
1×2
home 53.9% draw 25.8% away 20.3%
double_chance
1X 79.7% 12 74.2% X2 46.1%
dnb
home 72.6% away 27.4%
btts
yes 48.7% no 51.3%
clean_sheet
home 40.3% away 19.5%
win_to_nil
home 31.9% away 11.1%
winning_margin
home_by_1 24.5% home_by_2 16.8% home_by_3plus 12.6%
away_by_1 13.4% away_by_2 5.2% away_by_3plus 1.8%
correct_score
0-0 8.4% 0-1 6.6% 0-2 3.3%
0-3 1.0% 0-4 0.2% 0-5 0.0%
1-0 12.3% 1-1 12.3% 1-2 5.3%
1-3 1.6% 1-4 0.4% 1-5 0.1%
2-0 10.5% 2-1 9.5% 2-2 4.3%
2-3 1.3% 2-4 0.3% 2-5 0.1%
3-0 5.7% 3-1 5.2% 3-2 2.4%
3-3 0.7% 3-4 0.2% 3-5 0.0%
4-0 2.3% 4-1 2.1% 4-2 1.0%
4-3 0.3% 4-4 0.1% 4-5 0.0%
5-0 0.8% 5-1 0.7% 5-2 0.3%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 0.7%
likeliest_score
h 100.0% a 0.0% p 12.3%
Goals: totals / handicap / exact calibrated
total
over_0.5 91.6% under_0.5 8.4% over_1.5 72.7%
under_1.5 27.3% over_2.5 46.7% under_2.5 53.3%
over_3.5 25.2% under_3.5 74.8% over_4.5 11.5%
under_4.5 88.5% over_5.5 4.5% under_5.5 95.5%
odd_even
odd 48.5% even 51.5%
team_home
over_0.5 80.5% under_0.5 19.5% over_1.5 48.6%
under_1.5 51.4% over_2.5 22.6% under_2.5 77.4%
team_away
over_0.5 59.7% under_0.5 40.3% over_1.5 23.1%
under_1.5 76.9% over_2.5 6.4% under_2.5 93.6%
most
home 53.9% draw 25.8% away 20.3%
handicap
home_-2.5 12.6% away_+2.5 87.4% home_-1.5 29.4%
away_+1.5 70.6% home_-0.5 53.9% away_+0.5 46.1%
home_+0.5 79.7% away_-0.5 20.3% home_+1.5 93.1%
away_-1.5 7.0% home_+2.5 98.2% away_-2.5 1.8%
total_exact
exact_0 8.4% exact_1 18.8% exact_2 26.0%
exact_3 21.6% exact_4 13.7% exact_5 7.0%
exact_6 3.0% exact_7plus 1.5%
Method, limits & performance

How this works (honestly)

We are transparent about our method, our limits and how we measure performance.

What we use

Results, odds & closing prices, xG, shots, lineups, referee and schedule load.

Our method

Dixon-Coles + an xG strength model + champion/challenger selection + probability calibration + a trust gate.

What we don’t do

We do not beat the sharp market. The value is honest probabilities, No-bet calls and CLV.

Performance snapshot

Top-pick hit rate 47.7% (reliability, not edge). Calibration error 0.0106 (56038 matches).

Not financial advice. No model beats the sharp closing market on public data. The value here is honest probabilities, No-bet calls, and CLV history.

Explore this match