Wisla Plock vs Piast Gliwice prediction

Ekstraklasa
Wisla PlockWisla PlockWWLWL
Sat, 31 Oct 202631/1011:15UK
Piast GliwicePiast GliwiceWLWDW
32.8%Home winFair odds 3.05
29.1%DrawFair odds 3.44
38.2%Away winFair odds 2.62
Most likely published score1-113.7%Fair odds 7.28

MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Under 3.5 goalsBoth teams combined78.3%
Over 1.5 goalsBoth teams combined69.4%
Draw or Piast Gliwice67.3%

Early prediction · Model generated .

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

Piast Gliwice
Match winner (1X2)38.2%
Fair odds2.62
Save model pickSaved to my bets

Top signals

Goals marketUnder 3.5 goals
Model estimateModel78.3%
Fair oddsFair1.28
Double chance marketDraw or Piast Gliwice
Model estimateModel67.3%
Fair oddsFair1.49
Both teams to scoreNot both teams to score
Model estimateModel51.0%
Fair oddsFair1.96

Model read

An open result market: Piast Gliwice lead at 38.2%, with draw 29.1% and Wisla Plock at 32.8%. No result has a majority of the model probability. UnderRead full analysisShow less

An open result market: Piast Gliwice lead at 38.2%, with draw 29.1% and Wisla Plock at 32.8%. No result has a majority of the model probability. Under 2.5 goals is estimated at 57.5%, 13.7 percentage points above the matching market estimate. This is the most interesting supplied price difference in the eligible reads, not a demonstrated profitable edge. The overall match assessment has not cleared the model's betting filters; this market read does not override that decision.

Under 2.5 goals

Model estimate
57.5%
Matching market
43.8%
Difference
+13.7 pp
Fair odds
1.74
Recorded odds
2.15

Margin-adjusted comparison for this selection. The difference is in percentage points, not a proven return.

Not both teams to score

Model estimate
51.0%
Fair odds
1.96

Context & limits

  • Wisla Plock: 3 wins, 0 draws and 2 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Piast Gliwice: 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 1.4 goals. This is a historical sample, not a forecast for this fixture.
  • Recorded season averages: Wisla Plock 0.9 and Piast Gliwice 1.8 goals scored per game. These are team averages, not a forecast of this match total.
  • Prices are recorded observations. This view does not verify that the same price is still available now.
Additional match context

"When model and market disagree on Piast Gliwice, that gap is the story." Expect a tight one: the model splits Wisla Plock and Piast Gliwice almost evenly, Piast Gliwice marginally on top at 38%. Our number sits above the market's 27% for Piast Gliwice. The gap itself is information. This shapes as a low scoring affair: Over 2.5 is only 42% with both teams to score at 49%. Form guide over the last six: Wisla Plock W3 D1 L2, Piast Gliwice W4 D1 L1. History adds colour: across the last 5 meetings it is 2 wins for Wisla Plock, 0 draws and 3 for Piast Gliwice at 1.4 goals per match. The engine passes on this one (too extreme an outsider (fair 0.27)).

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.

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

3 wins · 0 draws · 2 losses

Piast GliwicePiast GliwiceLast 5
W
Win · 2-0
L
Loss · 1-2
W
Win · 2-1
D
Draw · 1-1
W
Win · 3-1

3 wins · 1 draw · 1 loss

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

2Wisla PlockWisla Plock wins
0Draws
3Piast GliwicePiast Gliwice wins
1.4Average goals
Date
Home team
Score
Away team
Piast GliwicePiast Gliwice
1 – 0
Wisla PlockWisla Plock
Wisla PlockWisla Plock
2 – 0
Piast GliwicePiast Gliwice
Piast GliwicePiast Gliwice
1 – 0
Wisla PlockWisla Plock
Wisla PlockWisla Plock
1 – 0
Piast GliwicePiast Gliwice
Wisla PlockWisla Plock
0 – 2
Piast GliwicePiast Gliwice

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

Model estimates and recorded bookmaker probabilities.

1X2 and Goals: Bet365 prices via API-Football, observed 28 Oct 2026, 13:46 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.

1X2

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 32.8%
Wisla Plock

Model minus market: -11.5 pp
Market probability: 44.3%
Model probability: 29.1%
Draw

Model minus market: +2.6 pp
Market probability: 26.5%
Model probability: 38.2%
Piast Gliwice

Model minus market: +9.0 pp
Market probability: 29.3%

Goals

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 90.1%
Over 0.5 goals

Model minus market: -4.1 pp
Market probability: 94.2%
Model probability: 9.9%
Under 0.5 goals

Model minus market: +4.1 pp
Market probability: 5.8%
Model probability: 69.4%
Over 1.5 goals

Model minus market: -10.8 pp
Market probability: 80.1%
Model probability: 30.6%
Under 1.5 goals

Model minus market: +10.8 pp
Market probability: 19.9%
Model probability: 42.5%
Over 2.5 goals

Model minus market: -13.1 pp
Market probability: 55.6%
Model probability: 57.5%
Under 2.5 goals

Model minus market: +13.1 pp
Market probability: 44.4%
Model probability: 21.7%
Over 3.5 goals

Model minus market: -12.7 pp
Market probability: 34.4%
Model probability: 78.3%
Under 3.5 goals

Model minus market: +12.7 pp
Market probability: 65.6%
Model probability: 9.3%
Over 4.5 goals

Model minus market: -7.9 pp
Market probability: 17.3%
Model probability: 90.7%
Under 4.5 goals

Model minus market: +7.9 pp
Market probability: 82.7%
Model probability: 3.4%
Over 5.5 goals

Model minus market: -3.5 pp
Market probability: 6.9%
Model probability: 96.6%
Under 5.5 goals

Model minus market: +3.5 pp
Market probability: 93.1%
Model probability: 49.0%
Both teams to score · Yes

Model minus market: -9.1 pp
Market probability: 58.1%
Model probability: 51.0%
Both teams to score · No

Model minus market: +9.1 pp
Market probability: 41.9%

Cards

No estimates available for this market.

Corners

No estimates available for this market.

Shots

No estimates available for this market.

Bookmaker odds

Real bookmaker price (APIF:Pinnacle:4) next to our model fair price. Bookmaker prices include the bookmaker margin, so our margin-free fair price usually looks longer. We do not claim to beat the closing market.

Gap is our probability minus the probability the bookmaker price implies (1 divided by the price), in percentage points. Because the price includes the margin, most gaps are negative. Model highlights are outcomes where our probability is at least 15 points higher. A gap is a disagreement, not a proven edge.

Match result · 1X2

Wisla Plock winBookmaker2.12Model fair3.05Model minus bookmaker probability, percentage points: -14.3 pp
DrawBookmaker3.41Model fair3.44Model minus bookmaker probability, percentage points: -0.2 pp
Piast Gliwice winBookmaker3.43Model fair2.62Model minus bookmaker probability, percentage points: +9.0 pp

Goals · 2.5

Over 2.5 goalsBookmaker1.70Model fair2.35Model minus bookmaker probability, percentage points: -16.3 pp
Under 2.5 goalsBookmaker2.15Model fair1.74Model minus bookmaker probability, percentage points: +10.9 pp

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

Wisla Plock win3.05
Draw3.44
Piast Gliwice win2.62
Both teams to score2.04

Goals

Over 0.5 goals1.11
Over 1.5 goals1.44
Over 2.5 goals2.35
Over 3.5 goals4.61
Wisla Plock most3.05
Piast Gliwice most2.62

Totals line guide

Both teams combined.

Over 0.590.1%Over 1.569.4%Over 2.542.5%Over 3.521.7%Over 4.59.3%Over 5.53.4%
Recommended focusOver 1.569.4%

Discipline: Fairly priced. Too extreme an outsider (fair 0.27).

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 90.1%
Fair odds Fair 1.11
Over 1.51.5 goals, Low risk
Model probability 69.4%
Fair odds Fair 1.44
Over 2.52.5 goals, High risk
Model probability 42.5%
Fair odds Fair 2.35
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-09.9%Fair odds 10.09 1-09.9%Fair odds 10.15 2-06.0%Fair odds 16.78 3-02.3%Fair odds 44.44 4-00.6%Fair odds 156.25 5-00.1%Fair odds 714.29
Away goals 1 0-110.9%Fair odds 9.19 1-113.7%Fair odds 7.28 2-17.4%Fair odds 13.48 3-12.8%Fair odds 35.71 4-10.8%Fair odds 126.58 5-10.2%Fair odds 555.56
Away goals 2 0-27.2%Fair odds 13.93 1-28.1%Fair odds 12.29 2-24.6%Fair odds 21.65 3-21.8%Fair odds 57.14 4-20.5%Fair odds 204.08 5-20.1%Fair odds 909.09
Away goals 3 0-33.0%Fair odds 33.56 1-33.4%Fair odds 29.59 2-31.9%Fair odds 52.08 3-30.7%Fair odds 138.89 4-30.2%Fair odds 476.19 5-30.1%Fair odds 2,000.00
Away goals 4 0-40.9%Fair odds 107.53 1-41.1%Fair odds 95.24 2-40.6%Fair odds 166.67 3-40.2%Fair odds 434.78 4-40.1%Fair odds 1,666.67 5-40.0%Fair odds 10,000.00
Away goals 5 0-50.2%Fair odds 434.78 1-50.3%Fair odds 384.62 2-50.2%Fair odds 666.67 3-50.1%Fair odds 1,666.67 4-50.0%Fair odds 5,000.00 5-50.0%Fair odds ·

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-1
Model probability13.7%
Fair odds7.28
0-1
Model probability10.9%
Fair odds9.19
0-0
Model probability9.9%
Fair odds10.09

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.

Referee not confirmed

No referee assignment is confirmed in our data yet. We never guess one from past matches.

Season stats

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

Wisla PlockWisla Plock
Piast GliwicePiast Gliwice

Overview

Statistic
Wisla Plock
Piast Gliwice
League position
#11 of 18
#6 of 18
Matches played
11
12
Record W-D-L
4-2-5
6-2-4
Recent form
WWLWL
Last 5 matches
WLWDW
Last 5 matches
Current streak
L1
W1
Points per game
1.27
1.67
Record, home vs away
2-1-1
2-1-2
PPG, home vs away
1.75
1.40

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

Show all season statsHide season stats

Goals

Statistic
Wisla Plock
Piast Gliwice
Goals scored per game
0.91
1.83
Goals conceded per game
1.45
1.50
Scored, home vs away
1.00
1.00
Conceded, home vs away
0.75
1.20
1st half goals per game
0.45
0.75
2nd half goals per game
0.45
1.08

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

Shooting

Statistic
Wisla Plock
Piast Gliwice
Shots per game
12.9
14.9
Shots faced per game
15.2
17.0
Shots on target per game
4.2
4.8
1st half shots per game
5.5
6.6
2nd half shots per game
7.5
8.3

Scale: 0–20 shots per game. Each team uses the same scale independently.

Corners & discipline

Statistic
Wisla Plock
Piast Gliwice
Corners won per game
5.6
4.5
Fouls per game
12.6
11.0

0–10 corners per game; 0–20 fouls per game Each team uses the same scale independently.

Goal rates

Statistic
Wisla Plock
Piast Gliwice
Over 2.5 rate
45.5%
58.3%
BTTS rate
36.4%
58.3%
Clean sheets
27.3%
25.0%

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

League averages this season: 2.96 goals per match · Over 2.5 in 59.4% · BTTS in 65.1%. 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.

Wisla PlockWisla Plock
Wisla Plock: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.45 0.45 11
Goals concededConceded 0.55 0.91 11
Shots 5.5 7.5 11
Shots facedOpp. shots 6.6 8.6 11
Shots on targetOn target 1.8 2.4 11
Shots on target facedOpp. on target 1.9 2.2 11
Corners wonCorners 2.2 3.5 11
Corners concededOpp. corners 2.2 2.5 11
Yellow cardsYellows 0.4 1.0 11
Opponent yellow cardsOpp. yellows 0.6 1.4 11
Piast GliwicePiast Gliwice
Piast Gliwice: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.75 1.08 12
Goals concededConceded 0.42 1.08 12
Shots 6.6 8.3 10
Shots facedOpp. shots 7.2 9.8 10
Shots on targetOn target 2.3 2.7 11
Shots on target facedOpp. on target 2.4 3.1 11
Corners wonCorners 2.3 2.3 12
Corners concededOpp. corners 3.7 3.6 12
Yellow cardsYellows 0.6 1.2 11
Opponent yellow cardsOpp. yellows 0.6 0.6 11
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.

Wisla Plock clean sheet 28.8%
Piast Gliwice clean sheet 32.1%
Wisla Plock win to nil 18.8%
Piast Gliwice win to nil 22.2%

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 32.8% draw 29.1% away 38.2%
double_chance
1X 61.8% 12 70.9% X2 67.2%
dnb
home 46.2% away 53.8%
btts
yes 49.0% no 51.0%
clean_sheet
home 28.8% away 32.2%
win_to_nil
home 18.9% away 22.3%
winning_margin
home_by_1 19.2% home_by_2 9.3% home_by_3plus 4.2%
away_by_1 21.2% away_by_2 11.2% away_by_3plus 5.8%
correct_score
0-0 9.9% 0-1 10.9% 0-2 7.2%
0-3 3.0% 0-4 0.9% 0-5 0.2%
1-0 9.9% 1-1 13.7% 1-2 8.1%
1-3 3.4% 1-4 1.1% 1-5 0.3%
2-0 6.0% 2-1 7.4% 2-2 4.6%
2-3 1.9% 2-4 0.6% 2-5 0.2%
3-0 2.3% 3-1 2.8% 3-2 1.8%
3-3 0.7% 3-4 0.2% 3-5 0.1%
4-0 0.6% 4-1 0.8% 4-2 0.5%
4-3 0.2% 4-4 0.1% 4-5 0.0%
5-0 0.1% 5-1 0.2% 5-2 0.1%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 0.3%
likeliest_score
h 100.0% a 100.0% p 13.7%
Goals: totals / handicap / exact calibrated
total
over_0.5 90.1% under_0.5 9.9% over_1.5 69.4%
under_1.5 30.6% over_2.5 42.5% under_2.5 57.5%
over_3.5 21.7% under_3.5 78.3% over_4.5 9.3%
under_4.5 90.7% over_5.5 3.4% under_5.5 96.6%
odd_even
odd 48.3% even 51.7%
team_home
over_0.5 67.8% under_0.5 32.2% over_1.5 31.3%
under_1.5 68.7% over_2.5 10.7% under_2.5 89.4%
team_away
over_0.5 71.2% under_0.5 28.8% over_1.5 35.4%
under_1.5 64.6% over_2.5 13.1% under_2.5 87.0%
most
home 32.8% draw 29.1% away 38.2%
handicap
home_-2.5 4.2% away_+2.5 95.8% home_-1.5 13.5%
away_+1.5 86.5% home_-0.5 32.8% away_+0.5 67.2%
home_+0.5 61.8% away_-0.5 38.2% home_+1.5 83.0%
away_-1.5 17.0% home_+2.5 94.2% away_-2.5 5.8%
total_exact
exact_0 9.9% exact_1 20.7% exact_2 26.9%
exact_3 20.8% exact_4 12.4% exact_5 5.9%
exact_6 2.3% exact_7plus 1.1%
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