Widzew Łódź 2:3 Lech Poznań: xG & match report · Ekstraklasa

Sunday, 30/08/2026 at 20:15

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Match report · Ekstraklasa

Widzew Łódź Home 0.80 xG · 14 shots

Lech Poznań Away 1.89 xG · 14 shots

23 The scoreline reflected the chances

Lech Poznań were the model's likeliest winner before kick-off at 45%. They won 3–2. The biggest difference was Lech Poznań's attack: 1.89 xG against 1.48 projected (+0.41). Widzew Łódź produced 0.80 xG against 1.08 projected (−0.28).

Goals

6' Antoni Kozubal Lech Poznań · 0.31 xG chance 0–1
22' Allahyar Sayyadmanesh Lech Poznań · 0.22 xG chance 0–2
27' Karol Świderski Widzew Łódź · 0.42 xG chance 1–2
53' Mariusz Fornalczyk Widzew Łódź · 0.01 xG chance 2–2
90' Luis Palma Lech Poznań · 0.66 xG chance 2–3

The model against the result

priced before kick-off

Widzew Łódź: 25%
Draw: 30%
Lech Poznań: 45% What happened

Data coverage Both teams have the full 20-match model window available.

Projected vs produced

Expected goals

Widzew Łódź 1.08 0.80 -0.28

Lech Poznań 1.48 1.89 +0.41

Lech Poznań produced 0.41 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

Widzew Łódź Lech Poznań

Shots: 14; 14
On target: 7; 9
Inside the box: 5; 8
xG per shot: 0.06; 0.13
Open play xG: 0.64; 1.69
Set-piece xG: 0.19; 0.19
Penalties: —; —

Shot-level xG may differ from the published match total

The provider publishes the match total separately from its shot-by-shot values. Those values are rounded to two decimals and, leaving out penalties and own goals, add up to its non-penalty xG: 0.81 for Widzew Łódź and 1.89 for Lech Poznań.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

28 shots · 2.71 xG

Hover, focus or tap a shot to read it.

Widzew Łódź
Lech Poznań
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Widzew Łódź

1.61 xG created 1.36 xGA

W 0.67 created, 0.47 conceded against Piast Gliwice
D 2.49 created, 1.15 conceded against Motor Lublin
D 1.79 created, 1.54 conceded against Wisła Płock
W 1.10 created, 1.08 conceded against Jagiellonia Białystok
L 2.31 created, 2.09 conceded against MKS Korona Kielce
D 1.29 created, 1.83 conceded against Śląsk Wrocław

Lech Poznań

1.68 xG created 1.23 xGA

D 1.84 created, 0.72 conceded against MZKS Arka Gdynia
W 1.40 created, 0.50 conceded against Radomiak Radom
D 1.23 created, 3.24 conceded against Wisła Płock
D 0.79 created, 0.88 conceded against Cracovia
W 1.69 created, 0.99 conceded against Wieczysta Kraków
W 3.12 created, 1.06 conceded against Piast Gliwice

xG created xG conceded (xGA) W / D / L: the match result

Head to head

Widzew Łódź: 1 won · 0 drawn · 1 lost

Pre-match model & market record

4 opportunities flagged0 won4 lost

Lost
Lost
Lost
Lost

View pre-match record

The outcomes the model flagged on Widzew Łódź against Lech Poznań before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection	Price	Edge	Result
Under 2.5 goals	2.15	+16.0%	Lost
Under 1.5 goals	4.33	+4.1%	Lost
Draw	3.40	+3.5%	Lost
Both teams not to score	2.38	+2.1%	Lost

Pre-match model vs market

Outcome	Model	Market	Difference	Fair odds
Widzew Łódź	24.8%	29.5%	−4.8 pp	4.04
Draw	30.4%	26.9%	+3.5 pp	3.29
Lech Poznań	44.8%	43.6%	+1.2 pp	2.23

Other markets

Outcome	Model	Market	Difference	Fair odds
Both teams to score	57.0%	60.8%	−3.7 pp	1.75
Both teams not to score	43.0%	39.2%	+3.7 pp	2.33
Over 1.5 goals	76.9%	78.3%	−1.5 pp	1.30
Under 1.5 goals	23.1%	21.7%	+1.5 pp	4.32
Over 2.5 goals	48.4%	56.3%	−7.9 pp	2.06
Under 2.5 goals	51.6%	43.7%	+7.9 pp	1.94

Prices and probabilities are the ones stored before kick-off; nothing here is recalculated. Edge is the model's probability times the price, minus one, so a flagged outcome that lost is the ordinary case rather than a contradiction.

Model details

Show

Fit window: the last 20 matches, recency weighted (a match 107 days old counts half)
Widzew Łódź sample: 20 matches
Lech Poznań sample: 20 matches
Computed: 1 day before kick-off
Prices taken: 10 hours before kick-off

Limitations

The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.