Predictions / Football / Italy. Serie A / Bologna vs Inter

Bologna vs Inter Prediction, Odds & AI Betting Tips

Bologna Bologna
May 24, 2026 - 13:00
0.98
1.41
25% 30% 45%
Inter Inter

Final betting verdict

Different markets price efficiency differently — 1X2 can be a pass while goals markets still show edge.

  • No value on 1X2 (Inter vs. current odds)
  • Possible value: Under 2.5 (+25%+ EV at best odds)
  • Possible value: BTTS No (+25%+ EV at best odds)
  • Steam repriced this match — late money may have eaten remaining edge on the steamed side.
Moderate conviction (6/10) — one selective line, not a multi-market parlay.
Betting Primary Pick (highest +EV)
BTTS No — Value
EV +25%+ Model 51.1%
Steam vs. value
Market momentum is strong, but current odds may already be over-adjusted. Steam detected — model value on this line may be priced out.
This match appears on the market-movement board for aggressive line repricing — not because 1X2 is currently a positive-EV bet.
🔥 Strong steam · Bologna ↑ +20.7% · 14/14 · 99 A+
Market steam Strong
Current EV Negative
Closing line pressure High
Value remaining Limited
Secondary (balanced value): Under 2.5 (EV +25%+) — 57.2% Model
Lower EV than primary, but with higher model probability (more “stable” when shown).
Why The model prices Under 2.5 goals about 13.7 percentage points above closing implied — the main structural read vs. the line.

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Draw (1X2), Under 2.5 goals meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Under 2.5 goals by about 13.7 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Bologna (1X2) 24.5 26.1 -1.6
Draw (1X2) 30.2 26.5 +3.7
Inter (1X2) 45.3 47.4 -2.1
Over 2.5 goals 42.8 56.5 -13.7
Under 2.5 goals 57.2 43.5 +13.7
What this means

In plain terms: the model lands near 57.2% on Under 2.5 goals, while the closing snapshot implied about 43.5%. The difference — about 13.7 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Bologna (1X2) 3.72 3.72 0.0
Draw (1X2) 3.67 3.67 0.0
Inter (1X2) 2.05 2.05 0.0
Over 2.5 goals 1.71 1.71 0.0
Under 2.5 goals 2.22 2.22 0.0
Over / Under 2.5 Best value (+EV)
Over 2.5 42.8% · Under 2.5 57.2%
EV Over -25.1% · EV Under +25%+
Value lean: Under 2.5
1X2 Lean
Inter · Model 45.3%
implied 47.4%
Main consensus market · EV: -4.7%
Best available bookmaker line: +1.1% EV
Some outlier bookmaker prices may still show small theoretical value vs. the consensus line above.
Correct Score Insights Longshot / fun
Most Likely
0-1
Probability 12.9%
Correct score is high-variance — small stakes for fun only.
Betting decision (model vs. market EV)
Value opportunity — At least one market shows estimated +EV at current best decimal odds (threshold: 2.0%).
Total expected goals (xG sum) is in a borderline band — outcome variance is high. (ΣxG ≈ 2.39)
Decision strength: 6.0 / 10
  • Primary line identified (+1.0)
  • Primary EV above 10% (+1.0)
  • Max 1X2 prob under 50% (no dominant 1X2) (−1.0)
  • Draw probability above 30% (−0.5)
  • Two or more valid +EV lines at threshold (+0.5)
O/U 2.5: EV Over -25.1% · EV Under +25%+ (12 book pairs)
BTTS: EV Yes -21.8% · EV No +25%+
Should you bet on this match? Only where +EV is shown; always compare with your own limits.
OddsGPT Decision Engine v2.1.0(EV + Market Structure + Risk Adjustment) Check Odds at 1xBet

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Serie A
  • Fixture: Bologna vs Inter
  • Kickoff: 2026-05-24 13:00:00
  • 1X2 (model): Home 24.5% · Draw 30.2% · Away 45.3%
  • xG (showing): Bologna 0.98 — Inter 1.41 (total xG ≈ 2.39)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 51.1% · Implied: 40.2% · Probability edge: +10.9 pts · Est. EV: +27.8%
  • BTTS (model): Yes 48.9% · No 51.1%
  • Correct score (top bin): 0-1 (12.9%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Early match state can move realised goals away from pre-kick projections.

Best Bet + Reason

Primary pick from the decision engine: BTTS No.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

No pick is a guarantee; variance is especially large in scoreline markets.

FAQ

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

Risk Factors

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 24, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Serie A Serie A — Standings
# TEAM MP W D L PTS
1 Inter 38 27 6 5 87
2 Napoli 37 22 7 8 73
3 AC Milan 37 20 10 7 70
4 AS Roma 37 22 4 11 70
5 Como 37 19 11 7 68
6 Juventus 37 19 11 7 68
7 Atalanta 38 15 14 9 59
8 Bologna 38 16 8 14 56
9 Lazio 38 14 12 12 54
10 Udinese 37 14 8 15 50
11 Sassuolo 37 14 7 16 49
12 Torino 37 12 8 17 44
13 Parma 37 10 12 15 42
14 Fiorentina 38 9 15 14 42
15 Genoa 37 10 11 16 41
16 Cagliari 37 10 10 17 40
17 Lecce 37 9 8 20 35
18 Cremonese 37 8 10 19 34
19 Hellas Verona 37 3 12 22 21
20 Pisa 38 2 12 24 18
# TEAM MP GS GC +/- PTS
1 Inter 38 89 35 +54 87
2 Como 37 61 28 +33 68
3 Juventus 37 59 32 +27 68
4 AS Roma 37 57 31 +26 70
5 Napoli 37 57 36 +21 73
6 AC Milan 37 52 33 +19 70
7 Atalanta 38 51 36 +15 59
8 Bologna 38 49 46 +3 56
9 Sassuolo 37 46 49 -3 49
10 Udinese 37 45 47 -2 50
11 Torino 37 42 61 -19 44
12 Lazio 38 41 40 +1 54
13 Fiorentina 38 41 50 -9 42
14 Genoa 37 41 50 -9 41
15 Cagliari 37 38 52 -14 40
16 Cremonese 37 31 53 -22 34
17 Parma 37 27 46 -19 42
18 Lecce 37 27 50 -23 35
19 Pisa 38 26 71 -45 18
20 Hellas Verona 37 25 59 -34 21
# TEAM MP xG xGC +/- PTS
1 Inter 38 69.7 33.4 +36.3 87
2 Juventus 37 63.6 31.2 +32.4 68
3 Como 37 59.9 32.7 +27.2 68
4 AC Milan 37 57.9 40.5 +17.4 70
5 Atalanta 38 55.9 41.4 +14.5 59
6 AS Roma 37 52.1 38.3 +13.8 70
7 Napoli 37 47.9 36.2 +11.7 73
8 Fiorentina 38 48.9 46.1 +2.8 42
9 Bologna 38 42.6 44.0 -1.4 56
10 Lazio 38 39.8 42.0 -2.2 54
11 Genoa 37 44.3 47.0 -2.7 41
12 Torino 37 44.0 50.7 -6.7 44
13 Udinese 37 41.5 50.4 -8.9 50
14 Hellas Verona 37 34.5 45.3 -10.8 21
15 Sassuolo 37 41.7 54.1 -12.4 49
16 Cagliari 37 34.1 51.6 -17.5 40
17 Pisa 38 38.1 57.8 -19.7 18
18 Cremonese 37 34.0 55.4 -21.4 34
19 Parma 37 31.0 55.6 -24.6 42
20 Lecce 37 29.1 56.6 -27.5 35
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