Fredrikstad vs Rosenborg prediction

Eliteserien
FredrikstadFredrikstadDDDLL
Sat, 31 Oct 202631/1015:00UK
RosenborgRosenborgWWDWW
28.3%Home winFair odds 3.53
25.5%DrawFair odds 3.92
46.2%Away winFair odds 2.16
Most likely published score1-112.0%Fair odds 8.31

MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Over 1.5 goalsBoth teams combined78.6%
Draw or Rosenborg71.7%
Under 3.5 goalsBoth teams combined67.7%

Early prediction · Model generated .

Our verdict

Road2Sushi's own call on this match: the likeliest result, how confident the model is, its strongest signals and the reasons behind them.

Every percentage is a model estimate and every fair price is 1 divided by that estimate. Neither is a bookmaker offer, and a model call is not a proven edge over the market.

Model pick

Rosenborg
Match winner (1X2)46.2%
Fair odds2.16
Save model pickSaved to my bets

Top signals

Goals marketOver 1.5 goals
Model estimateModel78.6%
Fair oddsFair1.27
Double chance marketDraw or Rosenborg
Model estimateModel71.7%
Fair oddsFair1.39
Both teams to scoreBoth teams to score
Model estimateModel57.6%
Fair oddsFair1.74

Model read

Rosenborg lead the result estimates at 46.2%. The match still has meaningful room for a draw or an opponent win. Both teams to score stands out at 57.Read full analysisShow less

Rosenborg lead the result estimates at 46.2%. The match still has meaningful room for a draw or an opponent win. Both teams to score stands out at 57.6%. The estimate leans this way, with substantial uncertainty remaining. Without a complete matching price comparison, this is an event read rather than a verified price opportunity. The overall match assessment has not cleared the model's betting filters; this market read does not override that decision.

Both teams to score

Model estimate
57.6%
Fair odds
1.74

Over 2.5 goals

Model estimate
54.6%
Matching market
58.3%
Difference
-3.7 pp
Fair odds
1.83
Recorded odds
1.65

Margin-adjusted comparison for this selection. The difference is in percentage points, not a proven return.

Context & limits

  • Fredrikstad: 0 wins, 3 draws and 2 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Rosenborg: 4 wins, 1 draws and 0 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 2.6 goals. This is a historical sample, not a forecast for this fixture.
  • A complete matching price comparison is unavailable for this selection, so a price edge cannot be established.
Additional match context

"Fredrikstad or Rosenborg? We publish probabilities, not certainties." Our engine prices Rosenborg at 46% for 31 October 2026. Favourites, yes; certainties, no. The market is more convinced than we are, pricing Rosenborg at 52%. Caution noted. No strong lean on goals (55% Over 2.5). The interest, if any, lives elsewhere. The recent series reads 0 wins for Fredrikstad, 2 draws and 3 for Rosenborg over 5 games, 2.6 goals on average. The run in: Fredrikstad arrive W0 D3 L3, Rosenborg W5 D1 L0. The engine passes on this one (too extreme an outsider (fair 0.24)).

Form & head-to-head

Recent form uses each club’s available results in their stored order. Select a W/D/L result for details.

Head-to-head figures use their own recorded sample. Where individual results are available, the figures and journal cover the same meetings. Missing results are never counted as draws.

FredrikstadFredrikstadLast 5
D
Draw · 1-1
D
Draw · 1-1
D
Draw · 1-1
L
Loss · 2-3
L
Loss · 1-5

0 wins · 3 draws · 2 losses

RosenborgRosenborgLast 5
W
Win · 5-3
W
Win · 3-1
D
Draw · 1-1
W
Win · 3-0
W
Win · 3-0

4 wins · 1 draw · 0 losses

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

0FredrikstadFredrikstad wins
2Draws
3RosenborgRosenborg wins
2.6Average goals
Date
Home team
Score
Away team
RosenborgRosenborg
4 – 0
FredrikstadFredrikstad
FredrikstadFredrikstad
0 – 2
RosenborgRosenborg
RosenborgRosenborg
1 – 0
FredrikstadFredrikstad
FredrikstadFredrikstad
2 – 2
RosenborgRosenborg
RosenborgRosenborg
1 – 1
FredrikstadFredrikstad

Odds: model vs bookmaker

Every price for this match in one place: the model's probabilities next to the bookmaker's, the bookmaker's prices with our gap, and the model's own fair odds for each market.

Bookmaker probabilities are de-vigged (the margin is removed) and come from one bookmaker. A gap between the model and that bookmaker is a disagreement, not a proven edge. Fair odds are 1 divided by the model probability, not a bookmaker quote.

Model vs market

Model estimates and recorded bookmaker probabilities.

1X2, Goals and Corners: Bet365 prices via API-Football, observed 27 Oct 2026, 18:59 UTC, with the bookmaker margin taken out.

A market probability is the bookmaker's own price with its margin taken out, so the outcomes of each line add up to 100%. A gap from our model is a disagreement, not a proven edge: when we tested 1X2 and goal totals on matches the model had never seen, the bookmaker's closing price was more accurate. For corners, cards and shots we have no such test.

1X2

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 28.3%
Fredrikstad

Model minus market: +3.5 pp
Market probability: 24.8%
Model probability: 25.5%
Draw

Model minus market: +2.2 pp
Market probability: 23.3%
Model probability: 46.2%
Rosenborg

Model minus market: -5.7 pp
Market probability: 51.9%

Goals

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 93.7%
Over 0.5 goals

Model minus market: -2.3 pp
Market probability: 96.1%
Model probability: 6.3%
Under 0.5 goals

Model minus market: +2.4 pp
Market probability: 3.9%
Model probability: 78.6%
Over 1.5 goals

Model minus market: -4.2 pp
Market probability: 82.7%
Model probability: 21.4%
Under 1.5 goals

Model minus market: +4.2 pp
Market probability: 17.3%
Model probability: 54.6%
Over 2.5 goals

Model minus market: -6.0 pp
Market probability: 60.6%
Model probability: 45.4%
Under 2.5 goals

Model minus market: +6.0 pp
Market probability: 39.4%
Model probability: 32.3%
Over 3.5 goals

Model minus market: -6.1 pp
Market probability: 38.3%
Model probability: 67.7%
Under 3.5 goals

Model minus market: +6.1 pp
Market probability: 61.7%
Model probability: 16.3%
Over 4.5 goals

Model minus market: -3.6 pp
Market probability: 19.9%
Model probability: 83.7%
Under 4.5 goals

Model minus market: +3.6 pp
Market probability: 80.1%
Model probability: 7.1%
Over 5.5 goals

Model minus market: -1.7 pp
Market probability: 8.8%
Model probability: 92.9%
Under 5.5 goals

Model minus market: +1.7 pp
Market probability: 91.2%
Model probability: 57.6%
Both teams to score · Yes

Model minus market: -2.0 pp
Market probability: 59.6%
Model probability: 42.4%
Both teams to score · No

Model minus market: +2.0 pp
Market probability: 40.4%

Cards

No estimates available for this market.

Corners

No estimates available for this market.

Shots

No estimates available for this market.

Bookmaker odds

Real bookmaker price (APIF:Pinnacle:4) next to our model fair price. Bookmaker prices include the bookmaker margin, so our margin-free fair price usually looks longer. We do not claim to beat the closing market.

Gap is our probability minus the probability the bookmaker price implies (1 divided by the price), in percentage points. Because the price includes the margin, most gaps are negative. Model highlights are outcomes where our probability is at least 15 points higher. A gap is a disagreement, not a proven edge.

Match result · 1X2

Fredrikstad winBookmaker3.99Model fair3.53Model minus bookmaker probability, percentage points: +3.2 pp
DrawBookmaker3.90Model fair3.92Model minus bookmaker probability, percentage points: -0.1 pp
Rosenborg winBookmaker1.84Model fair2.16Model minus bookmaker probability, percentage points: -8.1 pp

Goals · 2.5

Over 2.5 goalsBookmaker1.65Model fair1.83Model minus bookmaker probability, percentage points: -5.9 pp
Under 2.5 goalsBookmaker2.27Model fair2.20Model minus bookmaker probability, percentage points: +1.3 pp

Model fair odds

Our published model probability as a decimal price (1 divided by probability). A fair model price, not a bookmaker quote. Only the supported 1X2 calibration pool is calibrated; other markets retain their model estimates.

Match result

Fredrikstad win3.53
Draw3.92
Rosenborg win2.16
Both teams to score1.74

Goals

Over 0.5 goals1.07
Over 1.5 goals1.27
Over 2.5 goals1.83
Over 3.5 goals3.10
Fredrikstad most3.53
Rosenborg most2.17

Totals line guide

Both teams combined.

Over 0.593.7%Over 1.578.6%Over 2.554.6%Over 3.532.3%Over 4.516.3%Over 5.57.1%
Recommended focusOver 1.578.6%

Discipline: Fairly priced. Too extreme an outsider (fair 0.24).

Read context

Both teams combined. Each bar uses the stored model estimate for that exact total-goals line. Missing estimates are unavailable; they are not zero.

Fair odds are the model’s own probability price, not a published bookmaker offer.

Market explorer

Model probabilities and fair odds.

Each bar is a specific Over selection for both teams combined. Its height is the model probability, on the same 0–100% scale.

Risk describes estimated likelihood, not profitability: low risk at least 62%, medium 48% to under 62%, high below 48%. Colors follow the actual estimate, even when a risk band is missing.

Up to four markets are selected from available model data, prioritising a spread of risk profiles. Fair odds are calculated from the model, not bookmaker prices: 1 divided by probability.

Scores are exact home-away outcomes from zero to five goals per team. Unavailable estimates stay blank; partial inputs are not expanded, inferred or normalised. Scores outside the matrix remain eligible for the top three.

Low riskMedium riskHigh risk

Goals

Over 1.51.5 goals, Low risk
Model probability 78.6%
Fair odds Fair 1.27
Over 2.52.5 goals, Medium risk
Model probability 54.6%
Fair odds Fair 1.83
Over 3.53.5 goals, High risk
Model probability 32.3%
Fair odds Fair 3.10
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-06.3%Fair odds 15.95 1-06.5%Fair odds 15.50 2-04.3%Fair odds 23.09 3-01.8%Fair odds 56.18 4-00.5%Fair odds 181.82 5-00.1%Fair odds 714.29
Away goals 1 0-18.7%Fair odds 11.45 1-112.0%Fair odds 8.31 2-17.1%Fair odds 14.14 3-12.9%Fair odds 34.48 4-10.9%Fair odds 112.36 5-10.2%Fair odds 454.55
Away goals 2 0-27.6%Fair odds 13.18 1-29.4%Fair odds 10.68 2-25.8%Fair odds 17.33 3-22.4%Fair odds 42.19 4-20.7%Fair odds 136.99 5-20.2%Fair odds 555.56
Away goals 3 0-34.1%Fair odds 24.21 1-35.1%Fair odds 19.65 2-33.1%Fair odds 31.85 3-31.3%Fair odds 77.52 4-30.4%Fair odds 250.00 5-30.1%Fair odds 1,000.00
Away goals 4 0-41.7%Fair odds 59.17 1-42.1%Fair odds 48.08 2-41.3%Fair odds 78.12 3-40.5%Fair odds 188.68 4-40.2%Fair odds 625.00 5-40.0%Fair odds 2,500.00
Away goals 5 0-50.5%Fair odds 181.82 1-50.7%Fair odds 147.06 2-50.4%Fair odds 238.10 3-50.2%Fair odds 588.24 4-50.1%Fair odds 2,000.00 5-50.0%Fair odds 10,000.00

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-1
Model probability12.0%
Fair odds8.31
1-2
Model probability9.4%
Fair odds10.68
0-1
Model probability8.7%
Fair odds11.45

Referee

One match referee is shown from an explicitly saved result or a fresh, identity-matched provider fixture. Previous referees are never used to guess an appointment. An API listing can change.

The referee’s totals count every completed match with this referee in our data: football-data.co.uk names the referee in English leagues, and API-Football names the referee of the same match (same teams, date and score) in every league from 2025/26. A rate needs at least 5 matches with that figure.

The team table shows each team’s published history with that same referee only. Matches, team cards per game and match cards per game are separate fields; their available samples can differ. Missing values are not zero. Cards include yellow and red cards in the current historical source.

Referee not confirmed

No referee assignment is confirmed in our data yet. We never guess one from past matches.

Season stats

2026 season. Recorded results, not model estimates.

FredrikstadFredrikstad
RosenborgRosenborg

Overview

Statistic
Fredrikstad
Rosenborg
League position
#11 of 16
#4 of 16
Matches played
24
24
Record W-D-L
8-5-11
12-4-8
Recent form
DDDLL
Last 5 matches
WWDWW
Last 5 matches
Current streak
L2
W2
Points per game
1.21
1.67
Record, home vs away
5-3-3
5-1-6
PPG, home vs away
1.64
1.33

PPG scale: 0–3 points per game. Each team uses the same scale independently.

Show all season statsHide season stats

Goals

Statistic
Fredrikstad
Rosenborg
Goals scored per game
1.21
1.92
Goals conceded per game
1.71
1.29
Scored, home vs away
1.27
1.50
Conceded, home vs away
1.09
1.42
1st half goals per game
0.67
0.96
2nd half goals per game
0.54
0.96

Scale: 0–3 goals or expected goals (xG) per game. Each team uses the same scale independently.

Shooting

Statistic
Fredrikstad
Rosenborg
Shots per game
11.6
14.4
Shots faced per game
14.7
13.3
Shots on target per game
3.8
5.4
1st half shots per game
6.0
7.3
2nd half shots per game
5.8
7.9

Scale: 0–20 shots per game. Each team uses the same scale independently.

Corners & discipline

Statistic
Fredrikstad
Rosenborg
Corners won per game
4.4
6.3
Fouls per game
10.6
13.2

0–10 corners per game; 0–20 fouls per game Each team uses the same scale independently.

Goal rates

Statistic
Fredrikstad
Rosenborg
Over 2.5 rate
54.2%
62.5%
BTTS rate
66.7%
41.7%
Clean sheets
12.5%
37.5%

Scale: 0–100% of recorded matches, not model estimates. Each team uses the same scale independently.

League averages this season: 3.21 goals per match · Over 2.5 in 62.5% · BTTS in 59.9%. Full league tables & stats →

First half / second half

Averages per game in this season’s league matches, split at half-time. Games is the number of each team’s matches with verified half data for that row; below five matches the row stays blank, and a missing value is never a zero.

Corners, shots on target and yellow cards per half come from the data provider’s half-by-half match statistics and are only used when the two halves add up to the full-time count. Cards are split by the minute they were shown, and first-half stoppage time counts as the first half. These are recorded results, not predictions.

In the Premier League, La Liga, Bundesliga, Serie A and Ligue 1 the shots per half come from a different source than the match shot totals, so the two can differ slightly.

FredrikstadFredrikstad
Fredrikstad: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.67 0.54 24
Goals concededConceded 0.79 0.92 24
Shots 6.0 5.8 18
Shots facedOpp. shots 6.7 7.8 18
Shots on targetOn target 1.6 2.1 20
Shots on target facedOpp. on target 1.8 2.7 20
Corners wonCorners 2.2 2.1 20
Corners concededOpp. corners 2.8 3.3 20
Yellow cardsYellows 0.5 1.2 22
Opponent yellow cardsOpp. yellows 0.6 1.1 22
RosenborgRosenborg
Rosenborg: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.96 0.96 24
Goals concededConceded 0.54 0.75 24
Shots 7.3 7.9 18
Shots facedOpp. shots 5.6 7.8 18
Shots on targetOn target 3.0 2.9 17
Shots on target facedOpp. on target 2.4 2.7 17
Corners wonCorners 3.7 2.5 20
Corners concededOpp. corners 2.6 3.1 20
Yellow cardsYellows 0.7 1.2 21
Opponent yellow cardsOpp. yellows 0.5 1.4 21
All model outcomes · full market spectrum & player markets

Shots

Shots on target

Cards

Clean sheet & win to nil

Worked out from the scoreline grid above: a clean sheet is every scoreline where the other side fails to score. It is the model’s own percentage, scored against the result afterwards, and it is not a tip.

Fredrikstad clean sheet 19.5%
Rosenborg clean sheet 29.0%
Fredrikstad win to nil 13.3%
Rosenborg win to nil 22.7%

Full market spectrum · model probabilities

The model’s own percentages, with no odds attached. The smaller markets are here so you can see everything we hold a number on, not because we claim an advantage in them. The colour says how close our percentages have landed to reality on matches the model had never seen. This is the raw model spectrum. Its match-result marginal can differ from the published 1X2 above; it does not replace the saved prediction.

Match result & goals calibrated
1×2
home 28.3% draw 25.5% away 46.2%
double_chance
1X 53.8% 12 74.5% X2 71.7%
dnb
home 38.0% away 62.0%
btts
yes 57.6% no 42.4%
clean_sheet
home 19.5% away 29.2%
win_to_nil
home 13.3% away 22.9%
winning_margin
home_by_1 16.3% home_by_2 8.1% home_by_3plus 3.9%
away_by_1 21.8% away_by_2 14.2% away_by_3plus 10.2%
correct_score
0-0 6.3% 0-1 8.7% 0-2 7.6%
0-3 4.1% 0-4 1.7% 0-5 0.5%
1-0 6.5% 1-1 12.0% 1-2 9.4%
1-3 5.1% 1-4 2.1% 1-5 0.7%
2-0 4.3% 2-1 7.1% 2-2 5.8%
2-3 3.1% 2-4 1.3% 2-5 0.4%
3-0 1.8% 3-1 2.9% 3-2 2.4%
3-3 1.3% 3-4 0.5% 3-5 0.2%
4-0 0.5% 4-1 0.9% 4-2 0.7%
4-3 0.4% 4-4 0.2% 4-5 0.1%
5-0 0.1% 5-1 0.2% 5-2 0.2%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 0.8%
likeliest_score
h 100.0% a 100.0% p 12.0%
Goals: totals / handicap / exact calibrated
total
over_0.5 93.7% under_0.5 6.3% over_1.5 78.6%
under_1.5 21.4% over_2.5 54.6% under_2.5 45.4%
over_3.5 32.3% under_3.5 67.7% over_4.5 16.3%
under_4.5 83.7% over_5.5 7.1% under_5.5 92.9%
odd_even
odd 48.7% even 51.3%
team_home
over_0.5 70.9% under_0.5 29.2% over_1.5 34.9%
under_1.5 65.1% over_2.5 12.8% under_2.5 87.2%
team_away
over_0.5 80.5% under_0.5 19.5% over_1.5 48.6%
under_1.5 51.4% over_2.5 22.5% under_2.5 77.5%
most
home 28.3% draw 25.5% away 46.2%
handicap
home_-2.5 3.9% away_+2.5 96.1% home_-1.5 12.0%
away_+1.5 88.0% home_-0.5 28.3% away_+0.5 71.7%
home_+0.5 53.8% away_-0.5 46.2% home_+1.5 75.6%
away_-1.5 24.3% home_+2.5 89.8% away_-2.5 10.2%
total_exact
exact_0 6.3% exact_1 15.2% exact_2 24.0%
exact_3 22.3% exact_4 16.0% exact_5 9.2%
exact_6 4.4% exact_7plus 2.7%
Method, limits & performance

How this works (honestly)

We are transparent about our method, our limits and how we measure performance.

What we use

Results, odds & closing prices, xG, shots, lineups, referee and schedule load.

Our method

Dixon-Coles + an xG strength model + champion/challenger selection + probability calibration + a trust gate.

What we don’t do

We do not beat the sharp market. The value is honest probabilities, No-bet calls and CLV.

Performance snapshot

Top-pick hit rate 47.7% (reliability, not edge). Calibration error 0.0106 (56038 matches).

Not financial advice. No model beats the sharp closing market on public data. The value here is honest probabilities, No-bet calls, and CLV history.

Explore this match