Ligue 1

France · 2026/2027
Avg goals
0.00
BTTS
0.0%
Over 2.5
0.0%
Under 2.5
0.0%
H/D/A
0.0% / 0.0% / 0.0%

Top Over 2.5 teams

  1. Paris Saint-Germain FC0.0%
  2. Olympique de Marseille0.0%
  3. FC Lorient0.0%
  4. Espérance Sportive Troyes Aube Champagne0.0%
  5. AS Monaco FC0.0%

Top BTTS teams

  1. Paris Saint-Germain FC0.0%
  2. Olympique de Marseille0.0%
  3. FC Lorient0.0%
  4. Espérance Sportive Troyes Aube Champagne0.0%
  5. AS Monaco FC0.0%

Top Under 2.5 teams

  1. Paris Saint-Germain FC0.0%
  2. Olympique de Marseille0.0%
  3. FC Lorient0.0%
  4. Espérance Sportive Troyes Aube Champagne0.0%
  5. AS Monaco FC0.0%

This page is a season-long research hub for Ligue 1 (France, 2026/2027). Soccer Stats Hub brings together league averages, market trends and team-level signals so you can compare fixtures with context rather than relying on a single headline number.

Across the Ligue 1 season so far, matches are averaging 0.00 goals, both teams have scored in about 0.0% of games, roughly 0.0% of fixtures have gone Over 2.5 goals, about 0.0% have stayed Under 2.5 goals. These figures refresh as the 2026/2027 progresses and are a sensible starting point before you open individual matches.

Home teams have won 0.0% of games to date, with 0.0% drawn and 0.0% won by the away side. That home and away split often shapes how generous the goal markets look from one week to the next.

Paris Saint-Germain FC rank highly for Over 2.5 games. The tables below name the leading sides in each market before the interactive charts and fixture list load.

Ligue 1 stats guide

What can I research on this page?

Soccer Stats Hub tracks league averages, BTTS rates, Over and Under 2.5 trends, home advantage, standings, corners, cards, team rankings, player leaders and related fixture predictions where data is available. The goal is to show the evidence behind each market, not just the percentage in isolation.

How should I use these competition stats?

Start with the league-wide profile above, then compare team rankings, recent form and individual fixtures. A side can look strong on points yet weak on xG, or vice versa, so cross-check a few metrics before you settle on a view.

Where do the numbers come from?

Season and fixture data are drawn from established football statistics providers used across the site. Model outputs and probability views are described in our methodology page. Predictions are illustrative research tools, not guarantees of results.

Responsible use

Stats support informed judgement; they do not remove match-day risk. If you choose to bet, do so responsibly and within your limits. See our about page for more on how Soccer Stats Hub is built.