xG Statistics in Football Betting

xG (expected goals) statistics is a model that calculates the expected number of goals in football. It determines how many goals a team could have scored based on the level of threat posed by their attacks on the opponent’s goal. This data allows for a more objective assessment of the game.

The statistics are based on the fact that all shots on goal differ in their danger level. For instance, the probability of scoring from 11 meters is higher than from 40 meters. Shots on target have a higher danger coefficient than corner kicks. xG values range from 0 (no goal) to 1 (clear scoring chance) for each attack and are summed up for the entire match.

xG statistics are mainly used by football analysts, experts, and coaches. They also help bettors develop winning betting strategies. xG coefficients are publicly available.

Experts assign a danger coefficient using statistical data from thousands of similar shots, factoring in how often such attacks result in goals in football.

The calculation of expected goals (xG) also considers factors such as the shooting player’s position, the angle of the shot, and the distance to the goal. The pass quality to the attacking player and the ease of receiving the ball also affect the xG calculation. For instance, if a player takes a shot with their dominant foot, the likelihood of scoring is higher.

Experts use their evaluation factors to calculate expected goals (xG). While xG values may vary among analysts, the differences are generally minor. These calculated coefficients are then utilized to create different rankings. By using xG statistics, it is possible to predict a team’s potential position in a tournament if the actual number of goals scored aligns with the expected number.

Analyzing overall player form

For instance, if a football match concludes with one team winning 3-1, it may appear that the players performed exceptionally well. However, xG statistics indicate that the team’s offensive efforts were ineffective and feeble. 

This implies that the team was fortunate because they were up against a weaker opponent. In the next game, it’s improbable that the team will create more scoring opportunities. If they encounter an equally matched or stronger opponent, they will likely suffer a defeat.

Long-Term football forecasting

An alternative xG-based league table helps in making long-term forecasts. Suppose a team is in third place in the league but ranks only tenth in xG calculations. This indicates that the team is lucky or has strong attacking players.

As the tournament progresses, the situation will level out. Luck doesn’t last forever, so the team will likely start losing and move down the table.

Assessing prospects for underdogs

Before betting on an underdog, compare the league table with the alternative xG table. Sometimes, xG statistics rank clear underdogs, who started in tenth place or lower, much higher. The coefficient indicates the team’s ability to create dangerous scoring chances and conduct good attacks.

Considering expected goals, betting on the underdog to lose without scoring in the next matches is risky. Dangerous situations near the goal often lead to goals. An underdog with a high xG coefficient can score against the leader, even if they eventually lose the match.

Drawbacks of the xG Model

• It does not account for powerful attacks that do not end with a shot.

• A general formula is applied to players of all levels.

• It can provide a misleading impression of a team if used in isolation from other statistical data.

Compare coefficients over a period

Assessing a team’s capabilities based on the xG of a single game is impossible. Observe how the club performs over a season or at least several recent games. If the xG value consistently exceeds the number of goals scored, betting on a high total will be risky.

Teams with significant discrepancies between expected and actual results require special attention. In the short term, the statistics can be explained by a player’s injury, a change in coach, or another significant event. Professional athletes quickly adapt to new conditions, so results will soon stabilize.

If the discrepancy between the xG coefficient and the number of goals scored remains consistently significant over the long term, it reflects the team’s overall condition. This difference can be used as a basis for new football bets.

Analyze how the club plays against teams of similar level to the upcoming opponent

For example, a favorite and an underdog are set to play. The plan is to bet on the leader. Analyze the xG of the chosen club in matches against other underdogs. Often, leaders score fewer goals against weaker opponents than in games against equal competitors.

The reason lies in the underdog’s tactics: they take a solid defensive position, leaving many players on their half of the field. Many forwards find it challenging to shoot in such a situation. The leader gets bogged down in the opponent’s defense, and the match total remains low.

Where to find xG coefficients

Data on expected goals calculations are published on English-language websites. xG statistics for the Russian Premier League (RPL) and some European national leagues are available on understat.com. Coefficients are also published on Total Football Analysis, Between The Post, and other sites. Both paid and free resources are available. Paid services offer access to in-depth xG analysis and expert forecasts.