Statistics / Football / Italy. Serie A / Juventus vs Fiorentina

Juventus vs Fiorentina Statistics & Analysis

Juventus Juventus
May 17, 2026 - 10:00
0 1.93
2 0.78
xG Accuracy: 42%
Fiorentina Fiorentina
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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 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Juventus Fiorentina ✖ Incorrect
  • Correct Score Insights 1-0 0-2 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Serie A
  • Fixture: Juventus vs Fiorentina
  • Kickoff: 2026-05-17 13:00:00
  • 1X2 (model): Home 63.2% · Draw 23.7% · Away 13.1%
  • xG (showing): Juventus 1.93 — Fiorentina 0.78 (total xG ≈ 2.71)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 49.1% · Implied: 40.3% · Probability edge: +8.8 pts · Est. EV: +20.3%
  • BTTS (model): Yes 47.6% · No 52.4%
  • Correct score (top bin): 1-0 (12.8%)

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

Primary angle highlighted on the page: Under 2.5 goals.

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

Only one modest +EV edge is highlighted here; size cautiously and re-check if odds move.

FAQ

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

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.

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.

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 19, 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 A Serie A — Standings
# TEAM MP W D L PTS
1 Inter 37 27 5 5 86
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 37 15 13 9 58
8 Bologna 37 16 7 14 55
9 Lazio 37 13 12 12 51
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 Genoa 37 10 11 16 41
15 Fiorentina 37 9 14 14 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 37 2 12 23 18
# TEAM MP GS GC +/- PTS
1 Inter 37 86 32 +54 86
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 37 50 35 +15 58
8 Bologna 37 46 43 +3 55
9 Sassuolo 37 46 49 -3 49
10 Udinese 37 45 47 -2 50
11 Torino 37 42 61 -19 44
12 Genoa 37 41 50 -9 41
13 Fiorentina 37 40 49 -9 41
14 Lazio 37 39 39 0 51
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 Hellas Verona 37 25 59 -34 21
20 Pisa 37 25 69 -44 18
# TEAM MP xG xGC +/- PTS
1 Inter 37 69.7 33.4 +36.3 86
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 37 55.9 41.4 +14.5 58
6 AS Roma 37 52.1 38.3 +13.8 70
7 Napoli 37 47.9 36.2 +11.7 73
8 Fiorentina 37 48.9 46.1 +2.8 41
9 Bologna 37 42.6 44.0 -1.4 55
10 Lazio 37 39.8 42.0 -2.2 51
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 37 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
Serie A Italy. Serie A Predictions
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