Comparing Traditional vs Advanced Football Statistics

Football is more than just a game. It’s a passion, a religion, and a way of life for millions of people around the world. With its global appeal, the sport has seen numerous innovations and advancements over the years, including in the way its statistics are measured and analyzed. In this article, we will explore the differences between traditional and advanced football statistics and determine which one tells the whole story of a match.

Traditional Football Statistics

Traditional football statistics have been used for decades and are still the most commonly used metrics to measure a player’s or team’s performance. These statistics are simple and easy to understand, making them accessible to casual fans as well as experts.

The Common Traditional Football Statistics

• Goals scored
• Assists
• Shots on goal
• Possession percentage
• Passing accuracy
• Yellow and red cards
• Clean sheets

While these metrics are useful, they fail to provide a complete picture of a match. For example, a team that has a higher possession percentage may not necessarily be the better team if they don’t convert their possession into goals. Similarly, a player with a high passing accuracy may not have made any significant contributions to their team’s performance if their passes were not effective in creating scoring opportunities.

Advanced Football Statistics

Advanced football statistics, also known as analytics or metrics, are relatively new in the world of football. They use complex algorithms and machine learning techniques to analyze vast amounts of data to provide a more detailed and nuanced view of a match.

The Common Advanced Football Statistics

• Expected Goals (xG)
• Expected Assists (xA)
• Expected Points (xP)
• Passing Networks
• Pressing Intensity
• Goalkeeper Actions
• Player Movements

Expected Goals (xG) is one of the most popular advanced football statistics. It uses data such as the angle and distance of a shot, the position of the goalkeeper, and the number of defenders to calculate the likelihood of a shot resulting in a goal. Expected Assists (xA) is another metric that measures the probability of a pass resulting in a goal. Expected Points (xP) is a metric that predicts a team’s expected number of points based on their performance in a match.

Which One Tells the Whole Story?

Both traditional and advanced football statistics have their advantages and limitations. Traditional football statistics provide a straightforward and easy-to-understand summary of a match, making them accessible to a wider audience. Advanced football statistics, on the other hand, offer a more nuanced view of a match, taking into account a range of factors that traditional statistics overlook.

It’s important to note that no single statistic can tell the whole story of a match. Instead, it’s the combination of different metrics that provides a complete picture of a team’s or player’s performance.

Examples of How the Two Metrics Differ

Let’s take a look at a couple of examples to see how traditional and advanced football statistics differ and complement each other.

Example 1: A team has a possession percentage of 70%, but they lose the match 1-0.

Traditional statistics would suggest that the team with the higher possession percentage was the better team, but advanced statistics would reveal that the team failed to convert their possession into goals. Their xG may have been low, indicating that they did not create enough high-quality scoring chances. In this case, advanced statistics provide a more accurate representation of the match’s outcome.

Example 2: A striker has scored 15 goals in 20 matches.

Traditional statistics would suggest that the striker is having a great season, but advanced statistics would reveal that the striker may have been lucky or wasteful in front of goal. By looking at the striker’s xG, we can see if the goals he scored were from high-quality scoring chances or not. If the striker’s xG is lower than the number of goals he scored, it may indicate that he has been lucky or over-performing. On the other hand, if the striker’s xG is higher than the number of goals he scored, it may indicate that he has been wasteful and needs to improve his finishing.

Traditional Statistics

Traditional football statistics are the ones most commonly seen in match reports and used by fans to judge players’ performances. These statistics include:

• Goals scored
• Assists
• Shots on target
• Passing accuracy
• Tackles won
• Clean sheets (for goalkeepers)

While these statistics can provide a basic understanding of a team’s or player’s performance, they do not tell the whole story. A player may have a high passing accuracy, but if they are only making safe, short passes, they may not be contributing much to the team’s attacking play. Similarly, a team may have a high number of shots on target, but if they are all from long-range and easily saved by the goalkeeper, they are unlikely to score many goals.

Advanced Statistics

Advanced football statistics, on the other hand, aim to provide a more detailed and accurate analysis of a team’s or player’s performance. These statistics include:

• Expected goals (xG)
• Expected assists (xA)
• Pass completion percentage in the final third
• Successful dribbles
• Pressures
• Progressive passes and carries

Expected goals (xG) and expected assists (xA) are two of the most commonly used advanced statistics. xG measures the quality of a team’s scoring chances based on factors such as the location of the shot, the type of shot, and the number of defenders between the shooter and the goal. xA, on the other hand, measures the quality of a player’s passes that lead to a shot on goal.

By looking at these advanced statistics, we can get a better understanding of how a team or player is performing. For example, a team may have a low number of shots on target, but if their xG is high, it may indicate that they are creating high-quality scoring chances. Similarly, a player may have a low number of assists, but if their xA is high, it may indicate that they are making key passes that are leading to scoring chances.

Conclusion

While traditional statistics are still useful for providing a basic understanding of a team’s or player’s performance, advanced statistics provide a more detailed and accurate analysis. By using both traditional and advanced statistics, we can get a more complete picture of how a team or player is performing.

When comparing traditional vs advanced football statistics, it is important to remember that they are not mutually exclusive. Both types of statistics have their place in football analysis and can complement each other.

So next time you’re watching a match or analyzing a player’s performance, remember to look beyond the traditional statistics and delve deeper into the advanced statistics to get a more accurate and complete picture.