Otelul 1-1 Csikszereda M. Ciuc: result, our prediction

Liga I
OtelulOtelulDLLLL
Full time1-1Fri, 16 Oct 202616/1016:00UK
Csikszereda M. CiucCsikszeredaLLLLL
64.2%Home winFair odds 1.56
22.1%DrawFair odds 4.52
13.7%Away winFair odds 7.30
Pre-match: Most likely published score2-012.5%Fair odds 8.03

Pre-match model estimates · MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Otelul or draw86.3%
Over 1.5 goalsBoth teams combined75.8%
Under 3.5 goalsBoth teams combined71.2%

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.

OtelulOtelul
1-1FT
Csikszereda M. CiucCsikszereda

Match data

Match data: Otelul and Csikszereda M. Ciuc
OtelulOtelul Statistic Csikszereda M. CiucCsikszereda
1 Goals 1

The result, on the record

Recorded tally 2 of 5 published calls on this match were right.

Published calls · recorded grading

# Market Our pick Our chance Recorded grade
1 Match result Pick: Otelul Chance: 64.2% Wrong
2 Total goals 2.5 Pick: Over 2.5 Chance: 50.9% Wrong2 goals
3 Total goals 1.5 Pick: Over 1.5 Chance: 75.8% Correct2 goals
4 Total goals 3.5 Pick: Under 3.5 Chance: 71.2% Correct2 goals
5 Both teams to score Pick: No Chance: 53.3% 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

Otelul
Match winner (1X2)64.2%
Fair odds1.56
Save model pickSaved to my bets

Top signals

Double chance marketOtelul or draw
Model estimateModel86.3%
Fair oddsFair1.16
Goals marketOver 1.5 goals
Model estimateModel75.8%
Fair oddsFair1.32
Both teams to scoreNot both teams to score
Model estimateModel53.3%
Fair oddsFair1.88

Model read

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. Otelul lead the result estimateRead full analysisShow less

This match has been played. This is a historical snapshot of the pre-match estimates, not a current price opportunity. Otelul lead the result estimates at 64.2%. The match still has meaningful room for a draw or an opponent win. Otelul win is estimated at 64.2%, 8.2 percentage points above the matching market estimate. This is the most interesting supplied price difference in the eligible reads, not a demonstrated profitable edge. The overall match assessment has not cleared the model's betting filters; this market read does not override that decision.

Otelul win

Model estimate
64.2%
Matching market
56.0%
Difference
+8.2 pp
Fair odds
1.56
Recorded odds
1.65

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

Not both teams to score

Model estimate
53.3%
Fair odds
1.88

Over 2.5 goals

Model estimate
50.9%
Fair odds
1.96

Context & limits

  • Otelul: 0 wins, 1 draws and 4 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Csikszereda M. Ciuc: 0 wins, 0 draws and 5 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 3 recorded meetings averaged 3.3 goals. This is a historical sample, not a forecast for this fixture.
  • Prices are recorded observations. This view does not verify that the same price is still available now.
Additional match context

Few Liga I fixtures are this lopsided in the data: Otelul carry a 64% win probability against Csikszereda M. Ciuc on 16 October 2026. The numbers that frame it: • Notably, the model is warmer on Otelul than the market (56%). We flag disagreement rather than hide it. • Totals sit close to the fence: 51% for Over 2.5 with both teams to score at 47%. • Head to head, the last 3 meetings gave 1 wins for Otelul, 1 draws and 1 for Csikszereda M. Ciuc, averaging 3.3 goals a game. • The run in: Otelul arrive W1 D1 L4, Csikszereda M. Ciuc W0 D0 L6. The engine passes on this one (conservative EV -0.009 <= 0).

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.

OtelulOtelulLast 5
D
Draw · 2-2
L
Loss · 0-1
L
Loss · 0-3
L
Loss · 2-3
L
Loss · 0-1

0 wins · 1 draw · 4 losses

Csikszereda M. CiucCsikszeredaLast 5
L
Loss · 2-3
L
Loss · 1-5
L
Loss · 1-3
L
Loss · 0-2
L
Loss · 0-1

0 wins · 0 draws · 5 losses

W Win
D Draw
L Loss

Head-to-head

Last 3 meetings

1OtelulOtelul wins
1Draws
1Csikszereda M. CiucCsikszereda wins
3.3Average goals
Date
Home team
Score
Away team
OtelulOtelul
2 – 3
Csikszereda M. CiucCsikszereda
OtelulOtelul
3 – 0
Csikszereda M. CiucCsikszereda
Csikszereda M. CiucCsikszereda
1 – 1
OtelulOtelul

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, 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: 64.2%
Otelul

Model minus market: +8.2 pp
Market probability: 56.0%
Model probability: 22.1%
Draw

Model minus market: -4.4 pp
Market probability: 26.5%
Model probability: 13.7%
Csikszereda M. Ciuc

Model minus market: -3.9 pp
Market probability: 17.6%

Goals

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 92.9%
Over 0.5 goals

Model minus market: —
Market probability: —
Model probability: 7.1%
Under 0.5 goals

Model minus market: —
Market probability: —
Model probability: 75.8%
Over 1.5 goals

Model minus market: —
Market probability: —
Model probability: 24.2%
Under 1.5 goals

Model minus market: —
Market probability: —
Model probability: 50.9%
Over 2.5 goals

Model minus market: —
Market probability: —
Model probability: 49.1%
Under 2.5 goals

Model minus market: —
Market probability: —
Model probability: 28.8%
Over 3.5 goals

Model minus market: —
Market probability: —
Model probability: 71.2%
Under 3.5 goals

Model minus market: —
Market probability: —
Model probability: 13.9%
Over 4.5 goals

Model minus market: —
Market probability: —
Model probability: 86.1%
Under 4.5 goals

Model minus market: —
Market probability: —
Model probability: 5.8%
Over 5.5 goals

Model minus market: —
Market probability: —
Model probability: 94.2%
Under 5.5 goals

Model minus market: —
Market probability: —
Model probability: 46.7%
Both teams to score · Yes

Model minus market: —
Market probability: —
Model probability: 53.3%
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

Otelul winBookmaker1.65Model fair1.56Model minus bookmaker probability, percentage points: +3.5 pp
DrawBookmaker3.30Model fair4.52Model minus bookmaker probability, percentage points: -8.2 pp
Csikszereda M. Ciuc winBookmaker4.75Model fair7.30Model minus bookmaker probability, percentage points: -7.3 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

Otelul win1.56
Draw4.52
Csikszereda M. Ciuc win7.30
Both teams to score2.14

Goals

Over 0.5 goals1.08
Over 1.5 goals1.32
Over 2.5 goals1.96
Over 3.5 goals3.47
Otelul most1.56
Csikszereda M. Ciuc most7.28

Totals line guide

Both teams combined.

Over 0.592.9%Over 1.575.8%Over 2.550.9%Over 3.528.8%Over 4.513.9%Over 5.55.8%
Our stored model focusOver 1.575.8%

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 75.8%
Fair odds Fair 1.32
Over 2.52.5 goals, Medium risk
Model probability 50.9%
Fair odds Fair 1.96
Over 3.53.5 goals, High risk
Model probability 28.8%
Fair odds Fair 3.47
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-07.1%Fair odds 13.99 1-012.4%Fair odds 8.08 2-012.5%Fair odds 8.03 3-08.0%Fair odds 12.45 4-03.9%Fair odds 25.71 5-01.5%Fair odds 66.67
Away goals 1 0-14.7%Fair odds 21.46 1-110.5%Fair odds 9.54 2-19.7%Fair odds 10.36 3-16.2%Fair odds 16.05 4-13.0%Fair odds 33.22 5-11.2%Fair odds 85.47
Away goals 2 0-22.0%Fair odds 50.00 1-23.9%Fair odds 25.84 2-23.7%Fair odds 26.74 3-22.4%Fair odds 41.49 4-21.2%Fair odds 85.47 5-20.4%Fair odds 222.22
Away goals 3 0-30.5%Fair odds 192.31 1-31.0%Fair odds 100.00 2-31.0%Fair odds 103.09 3-30.6%Fair odds 161.29 4-30.3%Fair odds 333.33 5-30.1%Fair odds 833.33
Away goals 4 0-40.1%Fair odds 1,000.00 1-40.2%Fair odds 526.32 2-40.2%Fair odds 526.32 3-40.1%Fair odds 833.33 4-40.1%Fair odds 1,666.67 5-40.0%Fair odds 5,000.00
Away goals 5 0-50.0%Fair odds 5,000.00 1-50.0%Fair odds 3,333.33 2-50.0%Fair odds 3,333.33 3-50.0%Fair odds 5,000.00 4-50.0%Fair odds 10,000.00 5-50.0%Fair odds ·

Model’s 3 most likely score outcomes

Model probability · Fair odds

2-0
Model probability12.5%
Fair odds8.03
1-0
Model probability12.4%
Fair odds8.08
1-1
Model probability10.5%
Fair odds9.54

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 recorded

No verified match referee is available in the saved data.

Season stats

2026/27 season. Recorded results, not model estimates.

OtelulOtelul
Csikszereda M. CiucCsikszereda

Overview

Statistic
Otelul
Csikszereda M. Ciuc
League position
#14 of 16
#16 of 16
Matches played
11
11
Record W-D-L
2-4-5
0-1-10
Recent form
DLLLL
Last 5 matches
LLLLL
Last 5 matches
Current streak
L4
L6
Points per game
0.91
0.09
Record, home vs away
2-2-2
0-0-6
PPG, home vs away
1.33
0.00

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

Show all season statsHide season stats

Goals

Statistic
Otelul
Csikszereda M. Ciuc
Goals scored per game
1.00
0.55
Goals conceded per game
1.45
2.18
Scored, home vs away
1.17
0.50
Conceded, home vs away
1.17
2.50

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

Goal rates

Statistic
Otelul
Csikszereda M. Ciuc
Over 2.5 rate
45.5%
45.5%
BTTS rate
54.5%
36.4%
Clean sheets
9.1%
9.1%

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

League averages this season: 2.67 goals per match · Over 2.5 in 48.9% · BTTS in 46.6%. Full league tables & stats →

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.

Otelul clean sheet 45.4%
Csikszereda M. Ciuc clean sheet 14.5%
Otelul win to nil 38.2%
Csikszereda M. Ciuc win to nil 7.3%

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 64.2% draw 22.1% away 13.7%
double_chance
1X 86.3% 12 78.0% X2 35.8%
dnb
home 82.4% away 17.6%
btts
yes 46.7% no 53.3%
clean_sheet
home 46.1% away 14.4%
win_to_nil
home 38.9% away 7.3%
winning_margin
home_by_1 24.8% home_by_2 20.0% home_by_3plus 19.5%
away_by_1 9.6% away_by_2 3.2% away_by_3plus 0.9%
correct_score
0-0 7.1% 0-1 4.7% 0-2 2.0%
0-3 0.5% 0-4 0.1% 0-5 0.0%
1-0 12.4% 1-1 10.5% 1-2 3.9%
1-3 1.0% 1-4 0.2% 1-5 0.0%
2-0 12.5% 2-1 9.7% 2-2 3.7%
2-3 1.0% 2-4 0.2% 2-5 0.0%
3-0 8.0% 3-1 6.2% 3-2 2.4%
3-3 0.6% 3-4 0.1% 3-5 0.0%
4-0 3.9% 4-1 3.0% 4-2 1.2%
4-3 0.3% 4-4 0.1% 4-5 0.0%
5-0 1.5% 5-1 1.2% 5-2 0.4%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 1.5%
likeliest_score
h 200.0% a 0.0% p 12.5%
Goals: totals / handicap / exact calibrated
total
over_0.5 92.9% under_0.5 7.1% over_1.5 75.8%
under_1.5 24.2% over_2.5 50.9% under_2.5 49.1%
over_3.5 28.8% under_3.5 71.2% over_4.5 13.9%
under_4.5 86.1% over_5.5 5.8% under_5.5 94.2%
odd_even
odd 48.8% even 51.2%
team_home
over_0.5 85.6% under_0.5 14.4% over_1.5 57.6%
under_1.5 42.4% over_2.5 30.6% under_2.5 69.4%
team_away
over_0.5 53.9% under_0.5 46.1% over_1.5 18.2%
under_1.5 81.8% over_2.5 4.4% under_2.5 95.6%
most
home 64.2% draw 22.1% away 13.7%
handicap
home_-2.5 19.5% away_+2.5 80.5% home_-1.5 39.5%
away_+1.5 60.5% home_-0.5 64.2% away_+0.5 35.8%
home_+0.5 86.3% away_-0.5 13.7% home_+1.5 95.9%
away_-1.5 4.1% home_+2.5 99.1% away_-2.5 0.9%
total_exact
exact_0 7.1% exact_1 17.0% exact_2 24.9%
exact_3 22.1% exact_4 15.0% exact_5 8.1%
exact_6 3.7% exact_7plus 2.1%
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