Brann vs Ham-Kam Prediction

Brann
3-0
Finished
HT 1-0
Ham-Kam
Brann Stadion, Bergen· Mohammad Usman Aslam, Norway 16/08/2026
BrannBrann
3-0
Finished
Ham-KamHam-Kam

AI Best Pick

Statistical forecasts for entertainment purposes only - not betting or financial advice.

Data Quality
Complete
Match Importance
4.6 / 10
Value Analysis
69%Trust
Goals O/U
Under 3.5 Goals
1.61
SignalHIGHModel59%RiskMediumGap+10.3%
Brann Rest
4 days
Ham-Kam Rest
7 days

Match Forecasts

Match Result
1
58%1.57
X
24%4.20
2
18%5.20
Double Chance
1X
82%1.15
X2
42%2.35
Both Teams to Score
Yes
59%1.55
No
41%2.27
Goals
Projected Goals: 1.88 + 1.2 = 3.08
Over 1.5
84%1.14
Over 2.5
58%1.49
Over 3.5
32%2.25
Under 1.5
16%5.00
Under 2.5
42%2.46
Under 3.5
68%1.61
Corners
Projected Corners: 6.4 + 3.9 = 10.3
Over 8.5
64%1.19
Over 9.5
53%1.37
Over 10.5
43%1.62
Under 8.5
36%3.65
Under 9.5
47%2.75
Under 10.5
57%2.13
Cards
Projected Cards: 1.4 + 2.6 = 3.9
Over 3.5
45%-
Over 4.5
28%-
Under 3.5
55%-
Under 4.5
72%-

Match Events

4'Goal Disallowed - video reviewK. M. Ingason
19'B. Isufi
33'M. Gjone
42'B. Isufi INM. Johnsgard out
45+4'J. Soltvedt
62'K. M. Ingason
68'A. Trondsen INS. Nilsen out
68'H. Udahl IND. Moreira out
73'N. HolmAssist: K. M. Ingason
74'E. Gudmundsson INN. Wassberg out
78'N. Holm INB. Finne out
87'A. Potur INW. Osnes-Ringen out
87'F. Sjolstad IND. Al Saed out
90+1'K. M. Ingason INK. Kjartansson out
90+6'

Lineups

Brann
4-3-3Coach: Eirik Horneland
Ham-Kam
5-3-2Coach: Thomas Myhre
Mathias Dyngeland1M. DyngelandMathias Dyngeland
Denzel De Roeve21D. De RoeveDenzel De Roeve
Thore Pedersen23T. PedersenThore Pedersen
Vetle Dragsnes20V. DragsnesVetle Dragsnes
Joachim Soltvedt17J. SoltvedtJoachim Soltvedt
Kristian Eriksen16K. EriksenKristian Eriksen
Jacob Lungi Sørensen18J. Lungi SørensenJacob Lungi Sørensen
Eggert Aron Guðmundsson19E. Aron GuðmundssonEggert Aron Guðmundsson
Kristall Máni Ingason10K. Máni IngasonKristall Máni Ingason
Noah Jean Holm29N. Jean HolmNoah Jean Holm
Niklas Castro9N. CastroNiklas Castro
Marcus Sandberg12M. SandbergMarcus Sandberg
Patrick Metcalfe26P. MetcalfePatrick Metcalfe
Martin Gjone2M. GjoneMartin Gjone
Fredrik Sjolstad23F. SjolstadFredrik Sjolstad
Ethan Amundsen-Day3E. Amundsen-DayEthan Amundsen-Day
Viðar Ari Jónsson7V. Ari JónssonViðar Ari Jónsson
Aksel Baran Potur17A. Baran PoturAksel Baran Potur
Luc Mares14L. MaresLuc Mares
Anders Trondsen16A. TrondsenAnders Trondsen
Henrik Udahl19H. UdahlHenrik Udahl
Blerton Isufi29B. IsufiBlerton Isufi

Brann Substitutes

12Simen Vidtun NilsenG
6Cheick Mbacke DiopD
25Niklas Jensen WassbergM
7Kjartan Mar KjartanssonM
37Sondre Blumenfeldt VindenesM
43Brage Berg HaugenM
11Bård FinneF

Ham-Kam Substitutes

8Markus JohnsgardM
13Sander ØstraatG
5Aleksander AndresenD
22Snorre Strand NilsenD
10Loris MettlerM
6William Osnes-RingenM
24Danilo Al-SaedF
18Duarte MoreiraF

Match Stats

BrannHam-Kam
70%Ball Possession30%
10Corner Kicks1
1Yellow Cards1
0Red Cards1
24Total Shots3
11Shots on Goal0
4Shots off Goal2
17Shots Inside Box2
7Shots Outside Box1
9Blocked Shots1
10Fouls11
2Offsides0
0Goalkeeper Saves8
605Total Passes260
519Passes Accurate190
86%Pass Accuracy73%

Team Comparison

BrannBrann
Ham-KamHam-Kam
1658Elo Rating 1540
1.29Attack 1.49
1.67Defense 0.00
31%Hit Rate 17%
17.0Shots per Game 9.3
4.7Shots on Target 2.9
8.4Corners per Game 5.0
2.1Cards per Game 1.4

AI Insights

🏠Strong Home Advantage+119 Elo
High Goal Expectancy3.08 goals
📈BTTS Trend86% in H2H
📊Away Overperforming

Game State Tendencies

BrannBrann
  • Scores more in 2nd half (0.8 vs 0.4 in first half)
Ham-KamHam-Kam
  • Scores more in 2nd half (1 vs 0.5 in first half)
  • Concedes more in 2nd half - can tire late

Head to Head

Based on 5 historical meetings

Brann 81%Draw 19%0% Ham-Kam
3.56Avg Goals
86%BTTS Rate
66%Over 2.5

Referee Profile

Mohammad Usman Aslam, Norway · 20 matches analysed

3.8Avg Yellows
4.1Avg Cards
23.6Avg Fouls
Stricter than 15% of referees analysed

League Table

Eliteserien 2026
#TeamMPWDLGGDPtsForm
1Bodo/GlimtBodo/Glimt20162252:17+3550WWWWW
2VikingViking20152351:20+3147WDWLW
3MoldeMolde20113643:30+1336WWWWL
4TromsoTromso20105537:27+1035LLDLW
5LillestromLillestrom20102828:26+232WWLDL
6RosenborgRosenborg2093836:29+730WWLWW
7FredrikstadFredrikstad2083924:31-727DLWWW
8BrannBrann20821037:31+626LLDWW
9Sarpsborg 08 FFSarpsborg 08 FF2067723:26-325DDDLL
10Ham-KamHam-Kam2065927:41-1423LLDLD
11ValerengaValerenga20641033:42-922LDLDL
12KFUM OsloKFUM Oslo20641022:34-1222WLLDW
13SandefjordSandefjord20551018:27-920LDDWL
14Kristiansund BKKristiansund BK20541120:37-1719LWDLW
15AalesundAalesund2039831:45-1418LWLDD
16StartStart20441222:41-1916WLWLL
#TeamMPGPts
1Bodo/GlimtBodo/Glimt2052:1750
2VikingViking2051:2047
3MoldeMolde2043:3036
4TromsoTromso2037:2735
5LillestromLillestrom2028:2632
6RosenborgRosenborg2036:2930
7FredrikstadFredrikstad2024:3127
8BrannBrann2037:3126
9Sarpsborg 08 FFSarpsborg 08 FF2023:2625
10Ham-KamHam-Kam2027:4123
11ValerengaValerenga2033:4222
12KFUM OsloKFUM Oslo2022:3422
13SandefjordSandefjord2018:2720
14Kristiansund BKKristiansund BK2020:3719
15AalesundAalesund2031:4518
16StartStart2022:4116
Champions LeagueConference LeagueRelegation

Brann vs Ham-Kam Prediction

Our AI model has analysed this Eliteserien fixture using team Elo ratings, recent form, projected goals and head-to-head history. The forecasts cover six independent markets - each probability is a separate model calculation, not derived from the match winner result.

How to Read These Forecasts

Each percentage shows the model's calculated likelihood for that outcome. Above 65% indicates strong statistical confidence; 45-65% reflects a competitive or open market; below 45% suggests the outcome is statistically less likely. All figures are for informational and entertainment purposes only.

About Eliteserien

ScorePredicts covers Norway football across all major markets. Use the navigation to explore today's full fixture list or filter by market.

Key Factors for This Match

Brann and Ham-Kam have met 5 times recently, averaging 3.56 goals per game in those meetings. This forecast is based on a complete recent-form dataset for both teams.

All forecasts are generated by statistical and machine learning models for informational and entertainment purposes only. They are not guaranteed and do not constitute financial or betting advice.