Strasbourg vs Paris SG — Ligue 1 forecast, Saturday, 17 October 2026

Ligue 1·Saturday, 17 October 2026·15:15

vs

15:15

StrasbourgExpected goalsParis SG
0.94 xG2.01 xG

Metis Forecast

Market-anchored distribution

Model updated

Strasbourg

14%

Draw

17%

Paris SG

69%

Expected goals

0.94–2.01

Strasbourg · Paris SG

Paris SG win 69% of the current Metis Forecast. Most likely scores: 1–2 (13.9%), 0–1 (12.9%), 0–2 (11.7%).More forecast detail +

Both teams score in 54% of simulations.

Those three cover 39% of outcomes; the other 61% is spread across every remaining scoreline.

Strasbourg score at least twice in 24%; Paris SG in 63%.

Scoreline distribution

Match outcomes

Both teams score54%
Over 1.5 goals80%
Over 2.5 goals58%
Over 3.5 goals33%
Over 4.5 goals17%
Team scoring & clean sheets
Strasbourg clean sheet11%
Paris SG clean sheet39%
Strasbourg score 2+24%
Paris SG score 2+63%
Strasbourg score 3+7%
Paris SG score 3+32%

Model vs market

SourceHomeDrawAway
Raw Metis model26%26%47%
Market reference14%17%69%
Metis Forecast14%17%69%

Market reference: pinnacle, de-vigged (shin) · price snapshot .

The forecast combines the model’s scoreline structure with market information where a fresh price exists. The raw model is kept separate and benchmarked independently against the Pinnacle opening price.

Most likely scores

1–213.9%
0–112.9%
0–211.7%
1–17.9%
1–37.6%
0–36.4%

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Strasbourg

21 AugAvs Marseille0–4L
29 AugHvs Lens2–1W
6 SeptAvs Troyes6–2W
12 SeptHvs Monaco1–1D
19 SeptAvs Paris FC1–2L

Paris SG

23 AugAvs Rennes2–2D
28 AugAvs Lille2–2D
4 SeptHvs Monaco1–2L
13 SeptAvs Brest1–0W
20 SeptAvs Marseille2–1W

Head to head

No previous meetings in the Metis results archive for this competition.

Model context

StatStrasbourg
(Home · 2 matches)
Paris SG
(Away · 4 matches)
BTTS rate100.0%75.0%
Over 2.5 rate50.0%75.0%
Clean sheet0.0%25.0%
Avg goals2.503.00

Home stats use Strasbourg's home record; away stats use Paris SG's away record this season. These are completed-match rates over the samples shown above, not model probabilities — early in a season a handful of matches produces 0% and 100% readings.