Saturday, 13th August
Sunday, 14th August
Friday, 19th August
Saturday, 20th August
Expected Goals for Betting
This page brings you detailed and reliable Ligue 1 xG data. xG (Expected Goals) is a powerful metric for realising the probability that a shot will end up in the back of the net. You can view the meaning of xG on OddAlerts Insights. Analysing this data across a fixture, or season, can give you a true indication of team performance.
For example, if a team has recorded xG of 7.19 across their opening 4 fixtures but has scored just 2 goals, then this tells us that they are underperforming and should have scored more. We base this on the hundreds of thousands of shots that have been analysed.
For an introduction into xG, I would personally recommend this book by James Tippett. It was sent to me by a fellow OddAlerts user and just a couple of weeks later, I understood how important xG can be and this very page was built. This is just the start for xG and OddAlerts. Stay tuned on Telegram or Twitter for updates.
What Ligue 1 team has the best xG?
Paris Saint Germain is the best team for xG, with 4.12 and 4.12 per 90 minutes played this season. This means that they create good enough opportunities to be expected to score ~4.12 goals every game.
What Ligue 1 team has the best xGA (Expected Goals Against)?
Paris Saint Germain has the best xGA (0.19/90). This means they limit their opponents to chances that have a lower probability of scoring better than any other club. The total xGA for Paris Saint Germain is 0.19
What Ligue 1 team has the most xPTS (Expected Points)?
Paris Saint Germain is top of the table when it comes to xPTS, picking up 2.97 per 90 minutes played this season. Expected Points measures the number of points that Paris Saint Germain could have expected to take from a game given the scoring opportunities (xG) that they created and conceded.
Filter for xG, Odds, Form, Referee Stats, and More!
OddAlerts has developed one of the most powerful filtering tools around, allowing you to combine hundreds of different data points (now including xG) to find high-value football games.