Malmo FF 0-1 Hacken: result, our prediction

Allsvenskan
Malmo FFMalmo FFWDWLW
Full time0-1Sun, 18 Oct 202618/1015:30UK
HackenHackenLDDWW
43.0%Home winFair odds 2.33
25.2%DrawFair odds 3.97
31.9%Away winFair odds 3.13
Pre-match: Most likely published score1-111.6%Fair odds 8.59

Pre-match model estimates · MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Over 1.5 goalsBoth teams combined80.8%
Malmo FF or draw68.2%
Under 3.5 goalsBoth teams combined64.5%

Post-match analysis

Judged against the prediction this page published before kickoff. Right or wrong, it stays on the record.

A call is the side our published probability favoured. If we leaned towards under and three goals went in, that counts as a miss.

Malmo FFMalmo FF
0-1FT
HackenHacken

Match data

Match data: Malmo FF and Hacken
Malmo FFMalmo FF Statistic HackenHacken
0 Goals 1
0 Goals, 1st half 0
0 Goals, 2nd half 1

RefereeGlenn Nyberg

The result, on the record

Recorded tally 1 of 5 published calls on this match were right.

Published calls · recorded grading

# Market Our pick Our chance Recorded grade
1 Match result Pick: Malmo FF Chance: 43.0% Wrong
2 Total goals 2.5 Pick: Over 2.5 Chance: 57.9% Wrong1 goals
3 Total goals 1.5 Pick: Over 1.5 Chance: 80.8% Wrong1 goals
4 Total goals 3.5 Pick: Under 3.5 Chance: 64.5% Correct1 goals
5 Both teams to score Pick: Yes Chance: 60.7% Wrong

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

Malmo FF
Match winner (1X2)43.0%
Fair odds2.33
Save model pickSaved to my bets

Top signals

Goals marketOver 1.5 goals
Model estimateModel80.8%
Fair oddsFair1.24
Double chance marketMalmo FF or draw
Model estimateModel68.2%
Fair oddsFair1.47
Both teams to scoreBoth teams to score
Model estimateModel60.7%
Fair oddsFair1.65

Model read

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. An open result market: Malmo FFRead full analysisShow less

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. An open result market: Malmo FF lead at 43.0%, with draw 25.2% and Hacken at 31.9%. No result has a majority of the model probability. Both teams to score stands out at 60.7%. 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
60.7%
Fair odds
1.65

Over 2.5 goals

Model estimate
57.9%
Fair odds
1.73

Context & limits

  • Malmo FF: 3 wins, 1 draws and 1 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Hacken: 2 wins, 2 draws and 1 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 3.6 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

The model leans Malmo FF at 43% when Malmo FF host Hacken in the Allsvenskan on 18 October 2026. A lean, though, not a lock. The numbers that frame it: • Our number sits above the market's 37% for Malmo FF. The gap itself is information. • No strong lean on goals (58% Over 2.5). The interest, if any, lives elsewhere. • Recent form reads W3 D1 L2 for Malmo FF against W3 D2 L1 for Hacken. • Head to head, the last 5 meetings gave 2 wins for Malmo FF, 2 draws and 1 for Hacken, averaging 3.6 goals a game. Discipline says sit it out: outside trust zone (model prob 0.43, zone (0.45, 0.7)).

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.

Malmo FFMalmo FFLast 5
W
Win · 1-0
D
Draw · 0-0
W
Win · 4-1
L
Loss · 0-2
W
Win · 1-0

3 wins · 1 draw · 1 loss

HackenHackenLast 5
L
Loss · 1-3
D
Draw · 0-0
D
Draw · 1-1
W
Win · 5-0
W
Win · 3-0

2 wins · 2 draws · 1 loss

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

2Malmo FFMalmo FF wins
2Draws
1HackenHacken wins
3.6Average goals
Date
Home team
Score
Away team
HackenHacken
3 – 2
Malmo FFMalmo FF
HackenHacken
1 – 1
Malmo FFMalmo FF
Malmo FFMalmo FF
3 – 0
HackenHacken
Malmo FFMalmo FF
4 – 0
HackenHacken
HackenHacken
2 – 2
Malmo FFMalmo FF

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

Pre-match estimates, recorded before the match.

1X2: Bet365 prices, observed 18 Oct 2026, 11:35 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.

Every market price shown was recorded before kick-off.

1X2

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 43.0%
Malmo FF

Model minus market: +5.9 pp
Market probability: 37.1%
Model probability: 25.2%
Draw

Model minus market: +0.1 pp
Market probability: 25.1%
Model probability: 31.9%
Hacken

Model minus market: -6.0 pp
Market probability: 37.9%

Goals

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 94.5%
Over 0.5 goals

Model minus market: —
Market probability: —
Model probability: 5.5%
Under 0.5 goals

Model minus market: —
Market probability: —
Model probability: 80.8%
Over 1.5 goals

Model minus market: —
Market probability: —
Model probability: 19.2%
Under 1.5 goals

Model minus market: —
Market probability: —
Model probability: 57.9%
Over 2.5 goals

Model minus market: —
Market probability: —
Model probability: 42.1%
Under 2.5 goals

Model minus market: —
Market probability: —
Model probability: 35.5%
Over 3.5 goals

Model minus market: —
Market probability: —
Model probability: 64.5%
Under 3.5 goals

Model minus market: —
Market probability: —
Model probability: 18.6%
Over 4.5 goals

Model minus market: —
Market probability: —
Model probability: 81.4%
Under 4.5 goals

Model minus market: —
Market probability: —
Model probability: 8.5%
Over 5.5 goals

Model minus market: —
Market probability: —
Model probability: 91.5%
Under 5.5 goals

Model minus market: —
Market probability: —
Model probability: 60.7%
Both teams to score · Yes

Model minus market: —
Market probability: —
Model probability: 39.3%
Both teams to score · No

Model minus market: —
Market probability: —

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 (Bet365) 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.

After full time these are the stored pre-match prices, kept for the record. They are not current prices, so no outcome is highlighted.

Match result · 1X2

Malmo FF winBookmaker2.50Model fair2.33Model minus bookmaker probability, percentage points: +3.0 pp
DrawBookmaker3.60Model fair3.97Model minus bookmaker probability, percentage points: -2.5 pp
Hacken winBookmaker2.45Model fair3.13Model minus bookmaker probability, percentage points: -8.9 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

Malmo FF win2.33
Draw3.97
Hacken win3.13
Both teams to score1.65

Goals

Over 0.5 goals1.06
Over 1.5 goals1.24
Over 2.5 goals1.73
Over 3.5 goals2.82
Malmo FF most2.33
Hacken most3.14

Totals line guide

Both teams combined.

Over 0.594.5%Over 1.580.8%Over 2.557.9%Over 3.535.5%Over 4.518.6%Over 5.58.5%
Our stored model focusOver 1.580.8%

The stored model call was Fairly priced. The match has been played, so this is a historical snapshot: the graded result is below.

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 80.8%
Fair odds Fair 1.24
Over 2.52.5 goals, Medium risk
Model probability 57.9%
Fair odds Fair 1.73
Over 3.53.5 goals, High risk
Model probability 35.5%
Fair odds Fair 2.82
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-05.5%Fair odds 18.21 1-07.5%Fair odds 13.33 2-06.6%Fair odds 15.22 3-03.6%Fair odds 28.01 4-01.5%Fair odds 68.49 5-00.5%Fair odds 212.77
Away goals 1 0-16.2%Fair odds 16.03 1-111.6%Fair odds 8.59 2-19.0%Fair odds 11.06 3-14.9%Fair odds 20.33 4-12.0%Fair odds 49.75 5-10.7%Fair odds 153.85
Away goals 2 0-24.7%Fair odds 21.37 1-27.6%Fair odds 13.09 2-26.2%Fair odds 16.05 3-23.4%Fair odds 29.50 4-21.4%Fair odds 72.46 5-20.4%Fair odds 222.22
Away goals 3 0-32.2%Fair odds 46.51 1-33.5%Fair odds 28.49 2-32.9%Fair odds 34.97 3-31.6%Fair odds 64.10 4-30.6%Fair odds 158.73 5-30.2%Fair odds 476.19
Away goals 4 0-40.7%Fair odds 135.14 1-41.2%Fair odds 82.64 2-41.0%Fair odds 101.01 3-40.5%Fair odds 185.19 4-40.2%Fair odds 454.55 5-40.1%Fair odds 1,428.57
Away goals 5 0-50.2%Fair odds 500.00 1-50.3%Fair odds 303.03 2-50.3%Fair odds 370.37 3-50.2%Fair odds 666.67 4-50.1%Fair odds 1,666.67 5-50.0%Fair odds 5,000.00

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-1
Model probability11.6%
Fair odds8.59
2-1
Model probability9.0%
Fair odds11.06
1-2
Model probability7.6%
Fair odds13.09

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.

Recorded match referee.

Glenn Nyberg in our data
Per match All matches 2026
Matches 24 11
Goals 2.83 2.55
Yellow cards 3.83 3.55
Corners 10.3 9.2
Fouls 28.0 25.5
Both teams scored 63% 55%
Over 2.5 goals 46% 36%
Home wins 21% 18%
Latest 10 matches
Date Match Score Goals BTTS Yellow Red Corners Fouls
23 Oct 2026 Vasteras SK vs Halmstad 1-2 3 Yes 1 0 11 13
18 Oct 2026 Malmo FF vs Hacken 0-1 1 No 5 0 18 25
16 Sep 2026 AIK vs Mjallby 1-1 2 Yes 4 0 14 29
5 Sep 2026 GAIS vs Hacken 0-0 0 No 2 Not available 8 26
30 Aug 2026 AIK vs Hammarby 3-2 5 Yes 5 0 8 27
23 Aug 2026 Vasteras SK vs Kalmar 0-0 0 No 3 Not available 7 27
8 Aug 2026 Orgryte vs AIK 3-4 7 Yes 2 1 7 21
19 May 2026 Orgryte vs Goteborg 2-3 5 Yes 5 Not available 12 26
26 Apr 2026 Djurgarden vs Hammarby 1-1 2 Yes 2 Not available 3 28
17 Apr 2026 Degerfors vs Elfsborg 0-1 1 No 8 Not available 8 32

Glenn Nyberg referee stats

Team history with this referee
Team
Malmo FF Not available Not available Not available
Hacken Not available Not available Not available

No matching history for this referee is available for one or both teams.

Season stats

2026 season. Recorded results, not model estimates.

Malmo FFMalmo FF
HackenHacken

Overview

Statistic
Malmo FF
Hacken
League position
#6 of 16
#5 of 16
Matches played
23
23
Record W-D-L
11-3-9
10-9-4
Recent form
WDWLW
Last 5 matches
LDDWW
Last 5 matches
Current streak
W1
W2
Points per game
1.57
1.70
Record, home vs away
5-1-6
5-4-2
PPG, home vs away
1.33
1.73

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

Show all season statsHide season stats

Goals

Statistic
Malmo FF
Hacken
Goals scored per game
1.65
1.83
Goals conceded per game
1.43
1.30
Scored, home vs away
2.08
1.91
Conceded, home vs away
1.67
1.09

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

Goal rates

Statistic
Malmo FF
Hacken
Over 2.5 rate
60.9%
56.5%
BTTS rate
56.5%
56.5%
Clean sheets
34.8%
39.1%

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

League averages this season: 2.94 goals per match · Over 2.5 in 53.3% · BTTS in 51.6%. 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.

This match

This match by half: Malmo FF and Hacken
Malmo FF Hacken
Statistic 1H 2H 1H 2H
Goals 0 0 0 1
Malmo FFMalmo FF

Not enough verified half data for this team yet.

HackenHacken

Not enough verified half data for this team yet.

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.

Malmo FF clean sheet 25.1%
Hacken clean sheet 19.5%
Malmo FF win to nil 19.6%
Hacken win to nil 14.0%

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 43.0% draw 25.2% away 31.9%
double_chance
1X 68.1% 12 74.8% X2 57.0%
dnb
home 57.4% away 42.6%
btts
yes 60.7% no 39.3%
clean_sheet
home 25.2% away 19.6%
win_to_nil
home 19.7% away 14.1%
winning_margin
home_by_1 20.6% home_by_2 13.1% home_by_3plus 9.2%
away_by_1 17.3% away_by_2 9.3% away_by_3plus 5.2%
correct_score
0-0 5.5% 0-1 6.2% 0-2 4.7%
0-3 2.2% 0-4 0.7% 0-5 0.2%
1-0 7.5% 1-1 11.6% 1-2 7.6%
1-3 3.5% 1-4 1.2% 1-5 0.3%
2-0 6.6% 2-1 9.0% 2-2 6.2%
2-3 2.9% 2-4 1.0% 2-5 0.3%
3-0 3.6% 3-1 4.9% 3-2 3.4%
3-3 1.6% 3-4 0.5% 3-5 0.2%
4-0 1.5% 4-1 2.0% 4-2 1.4%
4-3 0.6% 4-4 0.2% 4-5 0.1%
5-0 0.5% 5-1 0.7% 5-2 0.4%
5-3 0.2% 5-4 0.1% 5-5 0.0%
other 1.0%
likeliest_score
h 100.0% a 100.0% p 11.6%
Goals: totals / handicap / exact calibrated
total
over_0.5 94.5% under_0.5 5.5% over_1.5 80.8%
under_1.5 19.2% over_2.5 57.9% under_2.5 42.1%
over_3.5 35.5% under_3.5 64.5% over_4.5 18.6%
under_4.5 81.4% over_5.5 8.5% under_5.5 91.5%
odd_even
odd 48.8% even 51.2%
team_home
over_0.5 80.4% under_0.5 19.6% over_1.5 48.5%
under_1.5 51.5% over_2.5 22.5% under_2.5 77.5%
team_away
over_0.5 74.8% under_0.5 25.2% over_1.5 40.0%
under_1.5 60.0% over_2.5 16.1% under_2.5 83.9%
most
home 43.0% draw 25.2% away 31.9%
handicap
home_-2.5 9.2% away_+2.5 90.8% home_-1.5 22.3%
away_+1.5 77.7% home_-0.5 43.0% away_+0.5 57.0%
home_+0.5 68.1% away_-0.5 31.9% home_+1.5 85.5%
away_-1.5 14.5% home_+2.5 94.8% away_-2.5 5.2%
total_exact
exact_0 5.5% exact_1 13.7% exact_2 22.9%
exact_3 22.4% exact_4 16.9% exact_5 10.1%
exact_6 5.1% exact_7plus 3.4%
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