· Eliteserien
Ham-Kam
ATT
5/10
DEF
4/10
vs
Rosenborg
5/10
ATT
6/10
DEF
Scheduled· Sat 24 Oct · 16:00

AI Match Analysis

Ham-Kam’s leaky defense gives Rosenborg a clear route to chances, while the hosts’ own attacking outlook points to a meaningful threat at home. With both sides projected to contribute and the match set up for an open exchange, the goal line appears likely to be surpassed.

Match GoalsOver 2.5
Best Pick
BTTS
62%
Correct Score
Top
1-1
10.4%
8.00
Top
2-1
9.4%
15.00
1-0
7.6%
19.00
1-2
7.1%
8.50
2-0
6.9%
29.00
2-2
6.4%
13.00
0-1
5.8%
9.50
3-1
5.6%
34.00
148%
4.75TOP
X23%
4.00
229%
1.61
1X71%
X252%
1277%
Confirmed XI5-4-1
12
Sandberg
22
Nilsen
2
Gjone
23
Sjølstad
27
Barros
5
Andresen
10
Mettler
14
Mares
26
Metcalfe
17
Potur
28
Benjamin
Impact Player Hot Head
Ham-Kam33 players
49.5/ 99Average
Top Rated
1K. LienFWD81
2William Osnes-RingenMID70
3Ilir KukleciDEF69
Rosenborg33 players
49.3/ 99Average
Top Rated
1Amin ChiakhaFWD73
2Ole Selnæs MID70
3Mads BomholtMID68
Player Rankings
Snipers
Top goal threats
1
K. LienHam-Kam
75
2
Amin ChiakhaRosenborg
70
3
Dino IslamovicRosenborg
65
4
Emil Konradsen CeideRosenborg
65
5
Noah Sahsah Rosenborg
62
Wall
Top defenders
1
Ilir KukleciHam-Kam
84
2
F. SjølstadHam-Kam
74
3
Håkon VoldenRosenborg
69
4
Håkon RøstenRosenborg
66
5
Ulrik Yttergård JenssenRosenborg
64
Control
Top playmakers
1
Ole Selnæs Rosenborg
87
2
Mathias KjøløRosenborg
67
3
William Osnes-RingenHam-Kam
54
4
Loris MettlerHam-Kam
53
5
V. JónssonHam-Kam
53
Bad Boys
Most likely to get booked
1
F. SjølstadHam-Kam
1
2
Aslak WitryRosenborg
1
3
Erlend Dahl ReitanRosenborg
1
4
Jesper Reitan-SundeRosenborg
1
5
G. SimenstadHam-Kam
4
Power Rankings
Strongest overall
1
K. LienHam-Kam
81
2
Amin ChiakhaRosenborg
73
3
William Osnes-RingenHam-Kam
70
4
Ole Selnæs Rosenborg
70
5
Ilir KukleciHam-Kam
69

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Ham-Kam vs Rosenborg based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the Ham-Kam vs Rosenborg match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If Ham-Kam has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for Ham-Kam vs Rosenborg without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives Ham-Kam a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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