Statistics / Football / France. Ligue 1 / Paris FC vs Paris Saint Germain

Paris FC vs Paris Saint Germain Statistics & Analysis

May 17, 2026 - 19:00
2 0.87
1 2.36
xG Accuracy: 50%
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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 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Paris Saint Germain Paris FC ✖ Incorrect
  • Correct Score Insights 0-2 2-1 ✖ Incorrect

AI match briefing

AI Match Summary

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

  • League: Ligue 1
  • Fixture: Paris FC vs Paris Saint Germain
  • Kickoff: 2026-05-16 19:00:00
  • 1X2 (model): Home 11.1% · Draw 19.5% · Away 69.5%
  • xG (showing): Paris FC 0.87 — Paris Saint Germain 2.36 (total xG ≈ 3.23)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 46.3% · Implied: 35.1% · Probability edge: +11.2 pts · Est. EV: +25.0%
  • BTTS (model): Yes 53.7% · No 46.3%
  • Correct score (top bin): 0-2 (11.0%)

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 pick from the decision engine: BTTS No.

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

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 18, 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
Ligue 1 Ligue 1Standings
# TEAM MP W D L PTS
1 Paris Saint Germain 33 24 4 5 76
2 Lens 33 21 4 8 67
3 Lille 33 18 7 8 61
4 Lyon 33 18 6 9 60
5 Rennes 33 17 8 8 59
6 Marseille 33 17 5 11 56
7 Monaco 33 16 6 11 54
8 Strasbourg 33 14 8 11 50
9 Lorient 33 11 12 10 45
10 Toulouse 33 12 8 13 44
11 Paris FC 33 10 11 12 41
12 Stade Brestois 29 33 10 8 15 38
13 Angers 33 9 8 16 35
14 Le Havre 33 6 14 13 32
15 Auxerre 33 7 10 16 31
16 Nice 33 7 10 16 31
17 Nantes 33 5 8 20 23
18 Metz 33 3 7 23 16
# TEAM MP GS GC +/- PTS
1 Paris Saint Germain 33 73 27 +46 76
2 Lens 33 62 35 +27 67
3 Marseille 33 60 44 +16 56
4 Rennes 33 58 47 +11 59
5 Monaco 33 56 49 +7 54
6 Lyon 33 53 36 +17 60
7 Strasbourg 33 53 43 +10 50
8 Lille 33 52 35 +17 61
9 Lorient 33 48 49 -1 45
10 Toulouse 33 47 46 +1 44
11 Paris FC 33 45 49 -4 41
12 Stade Brestois 29 33 42 54 -12 38
13 Nice 33 37 60 -23 31
14 Auxerre 33 32 44 -12 31
15 Metz 33 32 76 -44 16
16 Le Havre 33 30 44 -14 32
17 Nantes 33 29 52 -23 23
18 Angers 33 28 47 -19 35
# TEAM MP xG xGC +/- PTS
1 Paris Saint Germain 33 63.7 27.4 +36.3 76
2 Lens 33 66.7 42.7 +24.0 67
3 Marseille 33 60.2 42.1 +18.1 56
4 Lille 33 54.6 36.8 +17.8 61
5 Strasbourg 33 51.4 43.9 +7.5 50
6 Lyon 33 51.1 43.7 +7.4 60
7 Monaco 33 56.9 50.0 +6.9 54
8 Rennes 33 54.0 52.8 +1.2 59
9 Lorient 33 45.4 45.0 +0.4 45
10 Toulouse 33 42.9 42.6 +0.3 44
11 Stade Brestois 29 33 44.3 50.0 -5.7 38
12 Nantes 33 33.4 43.5 -10.1 23
13 Paris FC 33 44.4 56.1 -11.7 41
14 Le Havre 33 38.3 50.9 -12.6 32
15 Auxerre 33 35.5 48.1 -12.6 31
16 Nice 33 43.1 59.2 -16.1 31
17 Angers 33 32.4 55.4 -23.0 35
18 Metz 33 34.4 62.7 -28.3 16