HamKam 1:4 Tromsø IL: xG & match report · Eliteserien

Saturday, 18/07/2026 at 14:00

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Match report · Eliteserien

HamKam Home 0.80 xG · 6 shots

Tromsø IL Away 1.90 xG · 19 shots

14 The scoreline reflected the chances

Goals

28' Heine Asen Larsen Tromsø IL · 0.17 xG chance 0–1
47' Jens Hjertø-Dahl Tromsø IL · 0.04 xG chance 0–2
52' Ruben Jenssen Tromsø IL · 0.20 xG chance 0–3
58' Mame Alassane Niang HamKam · 0.31 xG chance 1–3
90' Ieltsin Camões Tromsø IL · 0.17 xG chance 1–4

The shots behind it

HamKam Tromsø IL

Shots: 6; 19
On target: 2; 6
Inside the box: 6; 14
xG per shot: 0.14; 0.10
Open play xG: 0.85; 1.85
Set-piece xG: 0.00; 0.04
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: 0.85 for HamKam and 1.90 for Tromsø IL.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

25 shots · 2.74 xG

Hover, focus or tap a shot to read it.

HamKam
Tromsø IL
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

HamKam

1.35 xG created 1.42 xGA

D 0.79 created, 1.11 conceded against Kristiansund BK
W 0.58 created, 1.53 conceded against Vålerenga IF
L 1.62 created, 1.03 conceded against Fredrikstad FK
W 1.29 created, 1.59 conceded against Lillestrøm SK
D 2.09 created, 2.40 conceded against Aalesunds FK
D 1.70 created, 0.83 conceded against Sandefjord Fotball

Tromsø IL

1.15 xG created 1.28 xGA

D 0.43 created, 0.92 conceded against IK Start
W 1.98 created, 1.16 conceded against Molde FK
L 0.11 created, 3.59 conceded against Bodø/Glimt
D 1.59 created, 0.90 conceded against Aalesunds FK
D 0.84 created, 0.36 conceded against KFUM Oslo
W 1.95 created, 0.77 conceded against Vålerenga IF

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

Head to head

HamKam: 0 won · 0 drawn · 2 lost

Model details

Show

The model never priced this match before kick-off, so there is no projection to read the result against.

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.