xgEdge

Sunday, 13/09/2026 at 17:00

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Match report · Ukrainian Premier League

Bukovyna Chernivtsi 1:1 Zoria Luhansk

Bukovyna Chernivtsi Home 2.31 xG
Zoria Luhansk Away 0.70 xG
11 Bukovyna Chernivtsi had the better chances, but it finished level

Bukovyna Chernivtsi were the model's likeliest winner before kick-off at 40%. It finished 1–1. The biggest difference was Zoria Luhansk's attack: 0.70 xG against 1.59 projected (−0.89). Bukovyna Chernivtsi produced 2.31 xG against 1.73 projected (+0.58).

The model against the result

priced before kick-off
Bukovyna Chernivtsi
40%
Draw
27% What happened
Zoria Luhansk
33%

Data coverage One of these teams has only 5 matches in the model window, short of the 10 the model wants. Read the projection as a direction rather than as a number.

Projected vs produced

Expected goals
Bukovyna Chernivtsi The model projected 1.73 Produced 2.31 Difference +0.58
Zoria Luhansk The model projected 1.59 Produced 0.70 Difference -0.89

Zoria Luhansk produced 0.89 xG less than projected

Projected before kick-off Produced on the night

The shots behind it

Bukovyna Chernivtsi Zoria Luhansk
Shots
22
8
On target
7
3
Inside the box
14
3
xG per shot
0.11
0.09

Recent form

Last 6 · xG per match
Bukovyna Chernivtsi

1.98 xG created 2.06 xGA

  • D 0.22 created, 3.49 conceded against LNZ Cherkasy
  • D 3.27 created, 0.04 conceded against Obolon Kyiv
  • L 2.83 created, 1.96 conceded against Karpaty Lviv
  • W 1.42 created, 2.62 conceded against Dynamo Kyiv
  • D 2.18 created, 2.19 conceded against FC Epicentr Dunaivtsi
Zoria Luhansk

1.41 xG created 1.21 xGA

  • D 0.66 created, 1.27 conceded against Metalist 1925
  • W 2.44 created, 0.84 conceded against Oleksandria
  • D 1.01 created, 1.64 conceded against Polissya Zhytomyr
  • W 2.46 created, 0.78 conceded against Kolos Kovalivka
  • W 0.83 created, 1.87 conceded against Polissya Zhytomyr
  • D 1.08 created, 0.87 conceded against Veres Rivne

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

Pre-match model & market record

7 opportunities flagged4 won3 lost

  • Won
  • Lost
  • Lost
  • Lost
  • Won
  • Won
  • Won
View pre-match record
The outcomes the model flagged on Bukovyna Chernivtsi against Zoria Luhansk before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection Price Edge Result
Both teams to score 1.83 +29.5% Won
Bukovyna Chernivtsi 2+ goals 2.20 +17.3% Lost
Zoria Luhansk 2+ goals 2.38 +15.2% Lost
Over 2.5 goals 1.73 +14.6% Lost
Zoria Luhansk to score 1.30 +6.5% Won
Bukovyna Chernivtsi to score 1.25 +5.7% Won
Over 1.5 goals 1.20 +5.3% Won

Pre-match model vs market

Outcome Model Market Difference Fair odds
Bukovyna Chernivtsi 39.9% 38.8% +1.1 pp 2.51
Draw 26.7% 26.2% +0.5 pp 3.74
Zoria Luhansk 33.4% 35.0% −1.5 pp 2.99

Other markets

Outcome Model Market Difference Fair odds
Bukovyna Chernivtsi to score 84.5% 75.0% +9.5 pp 1.18
Bukovyna Chernivtsi not to score 15.5% 25.0% −9.5 pp 6.47
Zoria Luhansk to score 82.0% 72.3% +9.6 pp 1.22
Zoria Luhansk not to score 18.0% 27.7% −9.6 pp 5.54
Both teams to score 70.6% 50.0% +20.6 pp 1.42
Both teams not to score 29.4% 50.0% −20.6 pp 3.41
Bukovyna Chernivtsi 2+ goals 53.3% 42.3% +11.0 pp 1.88
Bukovyna Chernivtsi at most 1 goal 46.7% 57.7% −11.0 pp 2.14
Zoria Luhansk 2+ goals 48.5% 39.2% +9.3 pp 2.06
Zoria Luhansk at most 1 goal 51.5% 60.8% −9.3 pp 1.94
Over 1.5 goals 87.8% 76.9% +10.8 pp 1.14
Under 1.5 goals 12.2% 23.1% −10.8 pp 8.17
Over 2.5 goals 66.4% 53.7% +12.7 pp 1.51
Under 2.5 goals 33.6% 46.3% −12.7 pp 2.97

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

· 1 warning
Show
Fit window
the last 20 matches, recency weighted (a match 107 days old counts half)
Bukovyna Chernivtsi sample
5 matches
Zoria Luhansk sample
20 matches
Computed
7 hours before kick-off
Prices taken
7 hours before kick-off

Warnings

  • Bukovyna Chernivtsi has only 5 matches in the database. Below 10 matches the estimate is very unreliable.

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.