Lech Poznan vs Zaglebie prediction

Ekstraklasa
Lech PoznanLech PoznanWWWWW
Sun, 8 Nov 20268/1119:15UK
ZaglebieZaglebieWLLWD
64.5%Home winFair odds 1.55
21.2%DrawFair odds 4.72
14.4%Away winFair odds 6.94
Most likely published score2-011.4%Fair odds 8.76

MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Lech Poznan or draw85.7%
Over 1.5 goalsBoth teams combined79.3%
Under 3.5 goalsBoth teams combined66.6%

Early prediction · Model generated · Bookmaker odds pending.

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

Lech Poznan
Match winner (1X2)64.5%
Fair odds1.55
Save model pickSaved to my bets

Top signals

Double chance marketLech Poznan or draw
Model estimateModel85.7%
Fair oddsFair1.17
Goals marketOver 1.5 goals
Model estimateModel79.3%
Fair oddsFair1.26
Both teams to scoreBoth teams to score
Model estimateModel50.9%
Fair oddsFair1.96

Model read

Lech Poznan lead the result estimates at 64.5%. The match still has meaningful room for a draw or an opponent win. Lech Poznan win stands out at 64.5%Read full analysisShow less

Lech Poznan lead the result estimates at 64.5%. The match still has meaningful room for a draw or an opponent win. Lech Poznan win stands out at 64.5%. 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.

Lech Poznan win

Model estimate
64.5%
Fair odds
1.55

Over 2.5 goals

Model estimate
55.8%
Fair odds
1.79

Both teams to score

Model estimate
50.9%
Fair odds
1.96

Context & limits

  • Lech Poznan: 5 wins, 0 draws and 0 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Zaglebie: 2 wins, 1 draws and 2 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 2.2 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

"64% on Lech Poznan is a measurement, not a promise." On paper this is one way traffic: the calibrated model makes Lech Poznan heavy favourites at 64% when Lech Poznan meet Zaglebie in the Ekstraklasa on 8 November 2026. Totals sit close to the fence: 56% for Over 2.5 with both teams to score at 51%. History adds colour: across the last 5 meetings it is 4 wins for Lech Poznan, 0 draws and 1 for Zaglebie at 2.2 goals per match. Fatigue may matter, with Lech Poznan 8 days shorter on recovery than Zaglebie. Recent form reads W5 D0 L1 for Lech Poznan against W3 D1 L2 for Zaglebie. The engine passes on this one (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.

Lech PoznanLech PoznanLast 5
W
Win · 5-1
W
Win · 4-1
W
Win · 6-1
W
Win · 2-1
W
Win · 3-1

5 wins · 0 draws · 0 losses

ZaglebieZaglebieLast 5
W
Win · 3-2
L
Loss · 0-2
L
Loss · 1-3
W
Win · 1-0
D
Draw · 2-2

2 wins · 1 draw · 2 losses

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

4Lech PoznanLech Poznan wins
0Draws
1ZaglebieZaglebie wins
2.2Average goals
Date
Home team
Score
Away team
ZaglebieZaglebie
0 – 1
Lech PoznanLech Poznan
Lech PoznanLech Poznan
1 – 2
ZaglebieZaglebie
Lech PoznanLech Poznan
3 – 1
ZaglebieZaglebie
ZaglebieZaglebie
0 – 1
Lech PoznanLech Poznan
Lech PoznanLech Poznan
2 – 0
ZaglebieZaglebie

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 probabilities

Model estimates and recorded bookmaker probabilities.

1X2

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 64.5%
Lech Poznan

Model minus market: —
Market probability: —
Model probability: 21.2%
Draw

Model minus market: —
Market probability: —
Model probability: 14.4%
Zaglebie

Model minus market: —
Market probability: —

Goals

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 94.1%
Over 0.5 goals

Model minus market: —
Market probability: —
Model probability: 5.9%
Under 0.5 goals

Model minus market: —
Market probability: —
Model probability: 79.3%
Over 1.5 goals

Model minus market: —
Market probability: —
Model probability: 20.7%
Under 1.5 goals

Model minus market: —
Market probability: —
Model probability: 55.8%
Over 2.5 goals

Model minus market: —
Market probability: —
Model probability: 44.2%
Under 2.5 goals

Model minus market: —
Market probability: —
Model probability: 33.4%
Over 3.5 goals

Model minus market: —
Market probability: —
Model probability: 66.6%
Under 3.5 goals

Model minus market: —
Market probability: —
Model probability: 17.1%
Over 4.5 goals

Model minus market: —
Market probability: —
Model probability: 82.9%
Under 4.5 goals

Model minus market: —
Market probability: —
Model probability: 7.6%
Over 5.5 goals

Model minus market: —
Market probability: —
Model probability: 92.4%
Under 5.5 goals

Model minus market: —
Market probability: —
Model probability: 50.9%
Both teams to score · Yes

Model minus market: —
Market probability: —
Model probability: 49.1%
Both teams to score · No

Model minus market: —
Market probability: —

Cards

No estimates available for this market.

Corners

No estimates available for this market.

Shots

No estimates available for this market.

Market comparison awaits bookmaker odds

Comparable bookmaker odds are not available for these outcomes yet.

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

Lech Poznan win1.55
Draw4.72
Zaglebie win6.94
Both teams to score1.96

Goals

Over 0.5 goals1.06
Over 1.5 goals1.26
Over 2.5 goals1.79
Over 3.5 goals2.99
Lech Poznan most1.55
Zaglebie most6.96

Totals line guide

Both teams combined.

Over 0.594.1%Over 1.579.3%Over 2.555.8%Over 3.533.4%Over 4.517.1%Over 5.57.6%
Recommended focusOver 1.579.3%

Discipline: Our price. No bookmaker price published for this match yet.

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 1.51.5 goals, Low risk
Model probability 79.3%
Fair odds Fair 1.26
Over 2.52.5 goals, Medium risk
Model probability 55.8%
Fair odds Fair 1.79
Over 3.53.5 goals, High risk
Model probability 33.4%
Fair odds Fair 2.99
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-05.9%Fair odds 16.98 1-010.6%Fair odds 9.41 2-011.4%Fair odds 8.76 3-07.8%Fair odds 12.80 4-04.0%Fair odds 24.94 5-01.7%Fair odds 60.61
Away goals 1 0-14.2%Fair odds 23.87 1-110.1%Fair odds 9.93 2-19.9%Fair odds 10.15 3-16.7%Fair odds 14.84 4-13.5%Fair odds 28.90 5-11.4%Fair odds 70.42
Away goals 2 0-22.0%Fair odds 49.50 1-24.1%Fair odds 24.15 2-24.3%Fair odds 23.53 3-22.9%Fair odds 34.36 4-21.5%Fair odds 67.11 5-20.6%Fair odds 163.93
Away goals 3 0-30.6%Fair odds 172.41 1-31.2%Fair odds 84.03 2-31.2%Fair odds 81.97 3-30.8%Fair odds 119.05 4-30.4%Fair odds 232.56 5-30.2%Fair odds 555.56
Away goals 4 0-40.1%Fair odds 769.23 1-40.3%Fair odds 384.62 2-40.3%Fair odds 384.62 3-40.2%Fair odds 555.56 4-40.1%Fair odds 1,111.11 5-40.0%Fair odds 2,500.00
Away goals 5 0-50.0%Fair odds 5,000.00 1-50.0%Fair odds 2,500.00 2-50.1%Fair odds 2,000.00 3-50.0%Fair odds 3,333.33 4-50.0%Fair odds 5,000.00 5-50.0%Fair odds 10,000.00

Model’s 3 most likely score outcomes

Model probability · Fair odds

2-0
Model probability11.4%
Fair odds8.76
1-0
Model probability10.6%
Fair odds9.41
1-1
Model probability10.1%
Fair odds9.93

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.

Lech PoznanLech Poznan
ZaglebieZaglebie

Overview

Statistic
Lech Poznan
Zaglebie
League position
#1 of 18
#8 of 18
Matches played
12
12
Record W-D-L
10-1-1
5-4-3
Recent form
WWWWW
Last 5 matches
WLLWD
Last 5 matches
Current streak
W5
D1
Points per game
2.58
1.58
Record, home vs away
6-1-0
1-3-2
PPG, home vs away
2.71
1.00

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

Show all season statsHide season stats

Goals

Statistic
Lech Poznan
Zaglebie
Goals scored per game
2.67
1.25
Goals conceded per game
0.92
1.25
Scored, home vs away
2.86
1.33
Conceded, home vs away
0.57
1.83
1st half goals per game
1.40
0.33
2nd half goals per game
1.30
0.92

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

Shooting

Statistic
Lech Poznan
Zaglebie
Shots per game
—
12.1
Shots faced per game
—
17.7
Shots on target per game
6.3
4.0
1st half shots per game
—
5.2
2nd half shots per game
—
6.9

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

Corners & discipline

Statistic
Lech Poznan
Zaglebie
Corners won per game
6.7
3.6
Cards per game
1.9
—
Fouls per game
12.0
12.9
Red cards this season
0
—

0–10 corners per game; 0–5 cards per game; 0–20 fouls per game Each team uses the same scale independently.

Goal rates

Statistic
Lech Poznan
Zaglebie
Over 2.5 rate
83.3%
50.0%
BTTS rate
75.0%
58.3%
Clean sheets
25.0%
33.3%

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

League averages this season: 2.98 goals per match · Over 2.5 in 60.7% · BTTS in 66.1%. 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.

Lech PoznanLech Poznan
Lech Poznan: season average per game by half
Per game 1H 2H Games
Goals scoredScored 1.40 1.30 10
Goals concededConceded 0.30 0.60 10
Shots on targetOn target 2.6 3.7 10
Shots on target facedOpp. on target 1.6 1.8 10
Corners wonCorners 3.9 2.8 10
Corners concededOpp. corners 2.0 2.5 10
Yellow cardsYellows 0.8 1.0 9
Opponent yellow cardsOpp. yellows 0.9 1.7 9
ZaglebieZaglebie
Zaglebie: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.33 0.92 12
Goals concededConceded 0.33 0.92 12
Shots 5.2 6.9 10
Shots facedOpp. shots 8.5 9.2 10
Shots on targetOn target 1.5 2.5 12
Shots on target facedOpp. on target 2.0 2.5 12
Corners wonCorners 1.8 1.8 12
Corners concededOpp. corners 2.8 3.1 12
Yellow cardsYellows 0.9 1.7 10
Opponent yellow cardsOpp. yellows 0.7 1.1 10
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.

Lech Poznan clean sheet 41.4%
Zaglebie clean sheet 12.8%
Lech Poznan win to nil 35.5%
Zaglebie win to nil 6.9%

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 64.5% draw 21.2% away 14.4%
double_chance
1X 85.6% 12 78.9% X2 35.5%
dnb
home 81.8% away 18.2%
btts
yes 50.9% no 49.1%
clean_sheet
home 42.2% away 12.8%
win_to_nil
home 36.3% away 6.9%
winning_margin
home_by_1 23.9% home_by_2 19.8% home_by_3plus 20.8%
away_by_1 9.8% away_by_2 3.5% away_by_3plus 1.1%
correct_score
0-0 5.9% 0-1 4.2% 0-2 2.0%
0-3 0.6% 0-4 0.1% 0-5 0.0%
1-0 10.6% 1-1 10.1% 1-2 4.1%
1-3 1.2% 1-4 0.3% 1-5 0.0%
2-0 11.4% 2-1 9.9% 2-2 4.3%
2-3 1.2% 2-4 0.3% 2-5 0.1%
3-0 7.8% 3-1 6.7% 3-2 2.9%
3-3 0.8% 3-4 0.2% 3-5 0.0%
4-0 4.0% 4-1 3.5% 4-2 1.5%
4-3 0.4% 4-4 0.1% 4-5 0.0%
5-0 1.7% 5-1 1.4% 5-2 0.6%
5-3 0.2% 5-4 0.0% 5-5 0.0%
other 1.9%
likeliest_score
h 200.0% a 0.0% p 11.4%
Goals: totals / handicap / exact calibrated
total
over_0.5 94.1% under_0.5 5.9% over_1.5 79.3%
under_1.5 20.7% over_2.5 55.8% under_2.5 44.2%
over_3.5 33.4% under_3.5 66.6% over_4.5 17.1%
under_4.5 82.9% over_5.5 7.6% under_5.5 92.4%
odd_even
odd 48.9% even 51.1%
team_home
over_0.5 87.2% under_0.5 12.8% over_1.5 60.8%
under_1.5 39.2% over_2.5 33.8% under_2.5 66.2%
team_away
over_0.5 57.8% under_0.5 42.2% over_1.5 21.4%
under_1.5 78.6% over_2.5 5.7% under_2.5 94.3%
most
home 64.5% draw 21.2% away 14.4%
handicap
home_-2.5 20.8% away_+2.5 79.2% home_-1.5 40.6%
away_+1.5 59.4% home_-0.5 64.5% away_+0.5 35.5%
home_+0.5 85.6% away_-0.5 14.4% home_+1.5 95.4%
away_-1.5 4.6% home_+2.5 98.9% away_-2.5 1.1%
total_exact
exact_0 5.9% exact_1 14.8% exact_2 23.5%
exact_3 22.4% exact_4 16.3% exact_5 9.5%
exact_6 4.6% exact_7plus 2.9%
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 47.8% (reliability, not edge). Calibration error 0.0106 (56049 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