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Eliteserien per 90 stats 2026/2027

Every Eliteserien player's season divided by the minutes he played, which is the only basis a regular and a substitute can be compared on.

Ranked from 270 minutes played.

Trent Kone Doherty leads on expected goal involvement per 90 minutes with 1.04, over 591 minutes played. That is 0.13 clear of Zlatko Tripić.

Showing 151–200 of 313 players

Eliteserien per 90 stats 2026/2027
# Player Club Min G/90 A/90 xG/90 xA/90 xGI/90
149 Martin Linnes Molde FK 834 0.11 0.11 0.07 0.14 0.21
149 Gianni Stensness Viking FK 1,665 0.22 0.00 0.16 0.05 0.21
149 Salim Laghzaoui Fredrikstad FK 896 0.00 0.10 0.16 0.05 0.21
149 Max Nilsson Fredrikstad FK 965 0.19 0.09 0.11 0.10 0.21
149 Tobias Moi Viking FK 857 0.00 0.00 0.09 0.12 0.21
149 Aslak Witry Rosenborg BK 1,012 0.09 0.00 0.09 0.12 0.21
157 Samukelo Kabini Molde FK 1,335 0.07 0.07 0.10 0.10 0.20
157 Jonas Lange Hjorth KFUM Oslo 1,181 0.00 0.23 0.06 0.14 0.20
157 Alexander Munksgaard Kristiansund BK 1,317 0.00 0.14 0.01 0.18 0.20
157 Edvard Pettersen Sandefjord Fotball 1,331 0.14 0.07 0.15 0.04 0.20
157 Eirik Wichne Sarpsborg 08 561 0.00 0.00 0.08 0.11 0.20
157 Sander Svendsen Kristiansund BK 549 0.16 0.16 0.08 0.11 0.20
157 Kristoffer Nessø Aalesunds FK 1,149 0.00 0.00 0.07 0.13 0.20
157 Herman Johan Haugen Viking FK 503 0.00 0.00 0.05 0.14 0.20
165 Elias Kristoffersen Hagen Vålerenga IF 1,671 0.11 0.05 0.14 0.05 0.19
165 Viðar Ari Jónsson HamKam 1,067 0.00 0.17 0.09 0.11 0.19
165 Bjorn Utvik Sarpsborg 08 1,800 0.00 0.05 0.10 0.09 0.19
165 Sander Hansen Sjøkvist KFUM Oslo 909 0.00 0.10 0.04 0.15 0.19
165 Martin Gjone HamKam 1,526 0.18 0.18 0.10 0.08 0.19
165 Marius Elvius Kristiansund BK 270 0.00 0.33 0.02 0.17 0.19
165 Aimar Sher Sarpsborg 08 1,541 0.06 0.00 0.04 0.14 0.19
172 Gustav Kjolstad Nyheim Lillestrøm SK 1,282 0.28 0.14 0.10 0.08 0.18
172 Villads Nielsen Bodø/Glimt 280 0.00 0.00 0.10 0.09 0.18
172 Tobias Hammer Svendsen Kristiansund BK 444 0.20 0.00 0.11 0.07 0.18
172 Magnus Westergaard Vålerenga IF 1,322 0.07 0.07 0.11 0.07 0.18
176 David Hickson Gyedu KFUM Oslo 459 0.00 0.20 0.05 0.12 0.17
176 Omar Jebali IK Start 820 0.00 0.22 0.05 0.12 0.17
176 Eric Kitolano Lillestrøm SK 739 0.00 0.00 0.05 0.12 0.17
176 Heine Gikling Bruseth Kristiansund BK 1,371 0.00 0.13 0.06 0.11 0.17
176 Julian Bakkeli Gonstad KFUM Oslo 428 0.21 0.00 0.17 0.00 0.17
181 Odin Thiago Holm Vålerenga IF 303 0.00 0.00 0.10 0.06 0.16
181 Hakon Helland Hoseth KFUM Oslo 1,360 0.26 0.13 0.12 0.04 0.16
181 Marcus Melchior Sandefjord Fotball 721 0.00 0.00 0.09 0.07 0.16
181 Eirik Haugan Molde FK 322 0.00 0.00 0.15 0.01 0.16
181 Ousmane Diallo Toure IK Start 1,219 0.22 0.00 0.09 0.07 0.16
181 Fredrik Holmé Fredrikstad FK 1,616 0.11 0.06 0.10 0.05 0.16
181 Tobias Solheim Dahl Rosenborg BK 822 0.00 0.11 0.00 0.15 0.16
188 Anders Baertelsen Viking FK 513 0.00 0.00 0.12 0.04 0.15
188 Mikael Ugland IK Start 1,379 0.00 0.07 0.04 0.11 0.15
188 Erlend Dahl Reitan IK Start 1,718 0.10 0.00 0.08 0.07 0.15
188 Claus Niyukuri Sarpsborg 08 1,341 0.13 0.27 0.09 0.07 0.15
188 Vetle Auklend Viking FK 635 0.00 0.00 0.01 0.14 0.15
188 John Olav Norheim IK Start 1,225 0.00 0.00 0.08 0.07 0.15
188 Anders Trondsen HamKam 689 0.13 0.00 0.06 0.09 0.15
188 Vetle Walle Egeli Sandefjord Fotball 1,723 0.00 0.10 0.05 0.09 0.15
188 Vetle Skjaervik Tromsø IL 1,297 0.07 0.07 0.08 0.07 0.15
188 Tobias Borkeeiet Sandefjord Fotball 360 0.25 0.00 0.02 0.13 0.15
198 Anders Hiim Sarpsborg 08 1,839 0.05 0.00 0.02 0.12 0.14
198 Ian Hoffmann HamKam 604 0.00 0.00 0.01 0.12 0.14
198 Martin Tangen Vinjor KFUM Oslo 1,244 0.00 0.29 0.10 0.04 0.14
  • under 90 minutes
About these figures What each column counts, and which feed it was counted from. Show
Min
Minutes played.
G/90
Goals per 90 minutes played.
A/90
Assists per 90 minutes played.
xG/90
Expected goals per 90 minutes played.
xA/90
Expected assists per 90 minutes played.
xGI/90
Expected goal involvement per 90 minutes played.

Appearances, minutes, goals, assists and shots on this page are summed over the Eliteserien matches we hold per-player figures for — the same matches the expected figures are summed over, so the two can be read against each other.

Learn how xgEdge calculates these figures →