Statistics / Football / Italy. Serie B / Reggiana vs Sampdoria

Reggiana vs Sampdoria Statistics & Analysis

Reggiana Reggiana
May 08, 2026 - 18:30
1 0.93
0 0.95
xG Accuracy: 76%
Sampdoria Sampdoria
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 draw Reggiana ✖ Incorrect
  • Correct Score Insights 0-0 1-0 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Serie B
  • Fixture: Reggiana vs Sampdoria
  • Kickoff: 2026-05-09 13:00:00
  • 1X2 (model): Home 31.7% · Draw 35.5% · Away 32.8%
  • xG (showing): Reggiana 0.93 — Sampdoria 0.95 (total xG ≈ 1.88)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 70.9% · Implied: 54.9% · Probability edge: +16.0 pts · Est. EV: +25.5%
  • BTTS (model): Yes 38.9% · No 61.1%
  • Correct score (top bin): 0-0 (15.3%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

Correct score remains high-variance even when a line is most likely on paper.

Best Bet + Reason

The engine’s headline primary is: Under 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

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

FAQ

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

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.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

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.

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 17, 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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Back to Statistics
Serie B Serie B — Standings
# TEAM MP W D L PTS
1 Venezia 38 24 10 4 82
2 Frosinone 38 23 12 3 81
3 Monza 38 22 10 6 76
4 Palermo 38 20 12 6 72
5 Catanzaro 38 15 14 9 59
6 Modena 38 15 10 13 55
7 Juve Stabia 38 11 18 9 51
8 Avellino 38 13 10 15 49
9 Mantova 38 13 7 18 46
10 Padova 38 12 10 16 46
11 Cesena 38 12 10 16 46
12 Carrarese 38 10 14 14 44
13 Sampdoria 38 11 11 16 44
14 Virtus Entella 38 10 12 16 42
15 Empoli 38 9 14 15 41
16 Sudtirol 38 8 17 13 41
17 Bari 38 10 10 18 40
18 Reggiana 38 9 10 19 37
19 Spezia 38 8 11 19 35
20 Pescara 38 7 14 17 35
# TEAM MP GS GC +/- PTS
1 Venezia 38 77 31 +46 82
2 Frosinone 38 76 34 +42 81
3 Catanzaro 38 62 51 +11 59
4 Monza 38 61 32 +29 76
5 Palermo 38 61 33 +28 72
6 Pescara 38 51 66 -15 35
7 Modena 38 49 36 +13 55
8 Carrarese 38 47 52 -5 44
9 Empoli 38 47 54 -7 41
10 Cesena 38 45 56 -11 46
11 Mantova 38 45 57 -12 46
12 Juve Stabia 38 44 45 -1 51
13 Avellino 38 43 55 -12 49
14 Spezia 38 43 59 -16 35
15 Padova 38 39 49 -10 46
16 Sudtirol 38 38 48 -10 41
17 Bari 38 38 60 -22 40
18 Virtus Entella 38 36 51 -15 42
19 Reggiana 38 36 56 -20 37
20 Sampdoria 38 35 48 -13 44
# TEAM MP xG xGC +/- PTS
1 Venezia 38 73.9 33.1 +40.8 82
2 Monza 38 56.5 34.9 +21.6 76
3 Palermo 38 57.5 43.0 +14.5 72
4 Frosinone 38 62.1 49.0 +13.1 81
5 Modena 38 49.2 38.5 +10.7 55
6 Cesena 38 51.7 46.5 +5.2 46
7 Sampdoria 38 38.6 35.7 +2.9 44
8 Empoli 38 46.3 44.1 +2.2 41
9 Juve Stabia 38 41.7 39.6 +2.1 51
10 Catanzaro 38 50.2 49.0 +1.2 59
11 Mantova 38 49.0 50.6 -1.6 46
12 Sudtirol 38 41.8 44.9 -3.1 41
13 Virtus Entella 38 45.0 48.5 -3.5 42
14 Spezia 38 46.9 50.5 -3.6 35
15 Carrarese 38 45.1 55.0 -9.9 44
16 Pescara 38 46.4 58.1 -11.7 35
17 Reggiana 38 33.8 48.8 -15.0 37
18 Avellino 38 33.6 51.9 -18.3 49
19 Padova 38 33.3 52.3 -19.0 46
20 Bari 38 33.3 61.8 -28.5 40
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