xgEdge

Friday, 21/08/2026 at 20:00

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Match report · HNL

NK Rudeš 4:1 NK Lokomotiva Zagreb

NK Rudeš Home 1.69 xG · 14 shots
NK Lokomotiva Zagreb Away 1.03 xG · 7 shots
41 The scoreline reflected the chances

NK Lokomotiva Zagreb were the model's likeliest winner before kick-off at 35%. NK Rudeš won 4–1. The biggest difference was NK Rudeš's attack: 1.69 xG against 1.28 projected (+0.41). NK Lokomotiva Zagreb produced 1.03 xG against 1.30 projected (−0.27).

Goals

  1. 28' Noa Skoko NK Rudeš · 0.07 xG chance 1–0
  2. 40' Dušan Vuković NK Lokomotiva Zagreb · 0.64 xG chance 1–1
  3. 53' Xavier Fernandes NK Rudeš · 0.56 xG chance 2–1
  4. 58' Josip Bralic NK Rudeš · 0.13 xG chance 3–1
  5. 65' Ivan Đorić NK Rudeš · 0.61 xG chance 4–1

The model against the result

priced before kick-off
NK Rudeš
34% What happened
Draw
31%
NK Lokomotiva Zagreb
35%

Data coverage One of these teams has only 3 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
NK Rudeš The model projected 1.28 Produced 1.69 Difference +0.41
NK Lokomotiva Zagreb The model projected 1.30 Produced 1.03 Difference -0.27

NK Rudeš produced 0.41 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

NK Rudeš NK Lokomotiva Zagreb
Shots
14
7
On target
6
1
Inside the box
10
4
xG per shot
0.12
0.15
Open play xG
0.90
0.93
Set-piece xG
0.82
0.13
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: 1.69 for NK Rudeš and 1.03 for NK Lokomotiva Zagreb.

Shot map

Both teams shown attacking the same goal for comparison.

NK Lokomotiva Zagreb · Dušan Vuković · 40' · Goal · 18 m · 0.64 xG NK Rudeš · Ivan Đorić · 65' · Goal · 2 m · 0.61 xG NK Rudeš · Xavier Fernandes · 53' · Goal · 5 m · 0.56 xG NK Lokomotiva Zagreb · Pavle Smiljanić · 82' · No goal · 13 m · 0.14 xG NK Rudeš · Josip Bralic · 58' · Goal · 7 m · 0.13 xG NK Lokomotiva Zagreb · Noa Godec · 36' · No goal · 7 m · 0.11 xG NK Rudeš · Vedran Celjak · 10' · No goal · 10 m · 0.10 xG NK Lokomotiva Zagreb · Kristijan Čabrajić · 82' · No goal · 12 m · 0.08 xG NK Rudeš · Noa Skoko · 28' · Goal · 13 m · 0.07 xG NK Lokomotiva Zagreb · Dušan Vuković · 90' · No goal · 19 m · 0.05 xG NK Rudeš · Jurica Poldrugač · 40' · No goal · 23 m · 0.04 xG NK Rudeš · Josip Bralic · 50' · No goal · 12 m · 0.04 xG NK Rudeš · Josip Bralic · 50' · No goal · 12 m · 0.04 xG NK Rudeš · Lenny Ilečić · 27' · No goal · 12 m · 0.03 xG NK Rudeš · Lenny Ilečić · 45' · No goal · 12 m · 0.03 xG NK Lokomotiva Zagreb · Athanasios Triantafyllou · 33' · No goal · 12 m · 0.02 xG NK Rudeš · Xavier Fernandes · 49' · No goal · 24 m · 0.02 xG NK Rudeš · Josip Bralic · 63' · No goal · 11 m · 0.02 xG NK Lokomotiva Zagreb · Pavle Smiljanić · 89' · No goal · 25 m · 0.02 xG NK Rudeš · Ante Pripuz Spekuljuk · 90' · No goal · 23 m · 0.02 xG NK Rudeš · Toni Kolega · 47' · No goal · 27 m · 0.01 xG

All shots

21 shots · 2.78 xG

Hover, focus or tap a shot to read it.

  • NK Rudeš
  • NK Lokomotiva Zagreb
  • Filled = goal
  • Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match
NK Rudeš

0.42 xG created 2.82 xGA

  • L 0.28 created, 2.33 conceded against HNK Rijeka
  • L 0.60 created, 2.76 conceded against NK Osijek
  • L 0.39 created, 3.38 conceded against GNK Dinamo Zagreb
NK Lokomotiva Zagreb

0.99 xG created 1.76 xGA

  • D 0.29 created, 0.75 conceded against NK Varaždin
  • D 1.50 created, 3.39 conceded against HNK Hajduk Split
  • D 0.95 created, 0.82 conceded against GNK Dinamo Zagreb
  • W 1.16 created, 2.35 conceded against NK Istra 1961
  • W 1.13 created, 1.54 conceded against HNK Gorica
  • L 0.92 created, 1.70 conceded against NK Osijek

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

Pre-match model & market record

8 opportunities flagged5 won3 lost

  • Won
  • Won
  • Lost
  • Won
  • Lost
  • Won
  • Lost
  • Won
View pre-match record
The outcomes the model flagged on NK Rudeš against NK Lokomotiva Zagreb before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection Price Edge Result
NK Rudeš to win 6.00 +103.4% Won
NK Rudeš 2+ goals 5.00 +86.9% Won
NK Lokomotiva Zagreb not to score 7.00 +71.3% Lost
NK Lokomotiva Zagreb at most 1 goal 2.50 +54.4% Won
Draw 4.20 +30.5% Lost
NK Rudeš to score 1.73 +29.3% Won
Under 2.5 goals 2.10 +7.3% Lost
Both teams to score 1.83 +7.0% Won

Pre-match model vs market

Outcome Model Market Difference Fair odds
NK Rudeš 33.9% 14.9% +19.0 pp 2.95
Draw 31.1% 21.3% +9.8 pp 3.22
NK Lokomotiva Zagreb 35.0% 63.8% −28.8 pp 2.85

Other markets

Outcome Model Market Difference Fair odds
NK Rudeš to score 74.9% 53.7% +21.2 pp 1.34
NK Rudeš not to score 25.1% 46.3% −21.2 pp 3.98
NK Lokomotiva Zagreb to score 75.5% 86.4% −10.9 pp 1.32
NK Lokomotiva Zagreb not to score 24.5% 13.6% +10.9 pp 4.09
Both teams to score 58.4% 50.0% +8.4 pp 1.71
Both teams not to score 41.6% 50.0% −8.4 pp 2.40
NK Rudeš 2+ goals 37.4% 18.9% +18.5 pp 2.68
NK Rudeš at most 1 goal 62.6% 81.1% −18.5 pp 1.60
NK Lokomotiva Zagreb 2+ goals 38.2% 62.5% −24.3 pp 2.61
NK Lokomotiva Zagreb at most 1 goal 61.8% 37.5% +24.3 pp 1.62
Over 1.5 goals 77.1% 76.6% +0.5 pp 1.30
Under 1.5 goals 22.9% 23.4% −0.5 pp 4.37
Over 2.5 goals 48.9% 55.3% −6.4 pp 2.05
Under 2.5 goals 51.1% 44.7% +6.4 pp 1.96

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)
NK Rudeš sample
3 matches
NK Lokomotiva Zagreb sample
20 matches
Computed
9 hours before kick-off
Prices taken
9 hours before kick-off

Warnings

  • NK Rudeš has only 3 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.