Player statistics

Types of player statistics

Player stats can be broadly categorised into several key areas, each providing a different perspective on a player’s performance. These categories often overlap, and a comprehensive analysis of a player’s abilities usually involves looking at a combination of different stats. Here are some of the most common types of player statistics:

Attacking player stats

These stats measure a player’s contributions to their team’s attacking play. They include:

• Goals: The number of goals a player has scored.
• Assists: The number of passes a player has made that directly led to a goal.
• Shots: The total number of shots a player has taken.
• Shots on target: The number of shots a player has taken that have been on target.
• Key passes: Passes that directly create a goal-scoring opportunity.
• Dribbles: The number of successful dribbles a player has completed.
• Crosses: The number of crosses a player has attempted.
• Through balls: Passes that split the defence and create a scoring chance.

Defensive player stats

These stats quantify a player’s contributions to their team’s defensive efforts. They include:

• Tackles: The number of successful tackles a player has made.
• Interceptions: The number of times a player has intercepted a pass.
• Clearances: The number of times a player has cleared the ball from danger.
• Blocks: The number of shots a player has blocked.
• Fouls committed: The number of fouls a player has committed.
• Aerial duels won: The number of aerial duels a player has won.

Passing Stats

These stats measure the accuracy and effectiveness of a player’s passing. They include:

• Passes completed: The total number of passes a player has completed.
• Pass accuracy: The percentage of passes a player has completed successfully.
• Key passes  (Also an attacking stat): Passes that directly create a goal-scoring opportunity.
• Long passes: The number of long passes a player has attempted and completed.
• Short passes: The number of short passes a player has attempted and completed.
• Successful passes: The number of passes a player has completed successfully.

Physical Stats

These stats track a player’s physical activity and stamina. They include:

• Distance covered: The total distance a player has covered during a match.
• Sprints: The number of sprints a player has made.
• Top speed: The highest speed a player has reached.

Other player stats

There are other types of player stats, including:

• Touches: The total number of times a player has touched the ball.
• Offsides: The number of times a player has been caught offside.
• Yellow/Red Cards: The number of yellow and red cards a player has received.

Interested in the player statistics available in the Sportmonks Football API? Check out our docs page.

How are player statistics collected?

The collection of player stats has become increasingly sophisticated over the years, evolving from manual observation to advanced technological methods. While some basic stats can still be tracked manually, the vast majority of data collection now relies on a combination of technologies and analytical tools. At Sportmonks, we manage all our data in the Sportmonks Scout Application Platform. Our dedicated scout teams from all over the world add, manage, and validate the data collected by this platform, while we collaborate with high-class data partners to ensure our football data is reliable and always up to date.

Here are some methods of data collection

• Manual (outdated) tracking: In the early days of football analysis, player stats were primarily collected through manual observation. Analysts would watch matches and record key events, such as goals, assists, tackles, and passes, using pen and paper. While this method is still used in some contexts, it is time-consuming, prone to human error, and limited in the amount of data that can be collected.
• Video analysis: Video analysis has become a crucial tool for collecting player stats. Matches are recorded from multiple angles, allowing analysts to review the action in detail and track player movements, ball possession, and various other events. Software tools are used to tag and annotate these events, making it easier to compile and analyse player stats. This process now incorporates VAR (Video Assistant Referee) technology, which provides independent reviews of key match decisions—like offside calls, fouls, and penalties—to ensure even greater accuracy in the recorded data. With VAR, data providers can further validate and refine their statistics, enhancing the overall reliability of player performance metrics.
• Optical tracking: Optical tracking systems use cameras placed around the stadium to track the precise movements of players and the ball. These systems can generate a wealth of data, including player positions, speed, distance covered, and ball possession. Optical tracking provides highly accurate and detailed information, allowing for a deeper understanding of player performance.
• Wearable technology: Wearable technology, such as GPS trackers and accelerometers, is increasingly used to monitor player performance and fitness. These devices can track various metrics, including distance covered, speed, heart rate, and acceleration. This data can be used to assess player fitness, monitor workload, and identify potential injuries.
• Football Data providers: Several companies specialise in collecting and providing football data. These data providers employ teams of analysts and use a combination of video analysis, optical tracking, and other technologies to compile comprehensive player stats. Their data is used by clubs, media organisations, and betting companies.
• Data integration: The various sources of player data are often integrated into a central database. This allows for a comprehensive analysis of player performance, combining information from different sources. Data visualisation tools are also used to present the data in a clear and understandable way, making it easier to identify trends and patterns.

Common use cases for player statistics

Player stats have become an integral part of modern football, influencing decision-making at all levels of the game. From player recruitment to tactical planning, player stats provide important insights that are used to improve performance and gain a competitive edge. Here are some of the key ways player stats are used

• Player evaluation and scouting: Player stats are useful for evaluating player performance and identifying potential targets for recruitment. Scouts use player stats to assess a player’s strengths and weaknesses, comparing them to other players in their position. For instance, a club like Man City that prioritizes keeping the ball is more likely to sign a player who not only boasts high passing accuracy and superior hold-up play but also demonstrates excellent off-ball movement and tactical intelligence.
• Tactical analysis and planning: Coaches use player stats to analyse their own team’s performance and identify areas for improvement. They can use stats to assess the effectiveness of different tactics, identify weaknesses in the opposition, and plan training sessions to address specific issues. A reference could be Liverpool switching players Cody Gakpo and Luis Diaz between centre forward and left-wing depending on the opposition to best maximize Gakpo’s height, strength threat and Diaz’s dynamism and trickery.
• Match analysis: Analysts use player stats to analyse individual matches, identifying key moments and understanding the factors that influenced the outcome (say, Chelsea’s highline against City, which cost them 2 goals). This information can be used to provide feedback to players, improve team performance, and gain insights into the opposition’s playing style.
• Performance monitoring and development: Player stats are used to monitor individual player performance over time. This allows coaches to track player progress, identify areas where they can improve, and tailor training programmes to their specific needs. Player stats can also be used to motivate players and provide them with objective feedback on their performance.
• Media and fan engagement: Player stats are widely used by media organisations to provide insights and analysis for fans. They can be used to compare players, track records, and provide context for match events. Football fans also engage in Fantasy football leagues that rely heavily on player stats and create another medium of entertainment.
• Contract negotiations: Player stats can play a role in contract negotiations, providing strong evidence of a player’s value. The better a player performs, the higher the chance of getting a more lucrative deal when they sign an extension or a new contract with a different team. Agents and clubs also use player stats to justify salary demands and negotiate transfer fees.
• Data-driven decision making: The increasing availability of player stats has led to a more data-driven approach to football management. Clubs are increasingly using data analytics to make informed decisions about player recruitment, tactical planning, and performance management. This trend is likely to continue as data collection and analysis become even more sophisticated,  and to help with all this, Sportmonks offers a comprehensive Football API that delivers real-time and historical player statistics from thousands of leagues worldwide.

The limitations of player stats

While player stats offer valuable insights into performance, it is important to acknowledge their limitations. Relying solely on numbers can lead to an incomplete or even misleading picture of a player’s true contribution. Here are some key limitations to consider:

• Context is very important: Stats don’t tell the whole story. A player’s performance needs to be considered within the context of the game, their team’s tactics, the opposition’s strength, and the specific role they are asked to play. For example, a player with a lower pass completion rate might be a creative playmaker like Bruno Fernandes in midfield attempting difficult, high-risk passes that create scoring opportunities, while a player with a high pass completion rate might be a defensive minded midfielder playing safe, simple passes that have little impact on the game.
• Factors you can’t quantify: Many important aspects of a player’s performance are difficult to quantify. These include things like leadership, communication, work rate, attitude, mental toughness and runs that drag players out of position in order to create a chance. These qualitative factors can have a significant impact on a team’s success but are not easily captured by traditional stats.
• Differences in players position: Comparing players across different positions using the same stats can be misleading. Forwards are judged on goals and assists, while defenders are judged on tackles and interceptions. Comparing these stats directly doesn’t provide a fair assessment of their relative contributions. Even within the same position, different players might have different roles and responsibilities (eg a false 9 vs a traditional 9), making direct comparisons difficult.
• The sample size: Stats can be misleading if the sample size is too small. A player might have a string of good or bad performances that are not representative of their overall ability. It’s important to look at stats over a longer period of time to get a more accurate picture of their performance.
• Data accuracy: The accuracy of player stats depends on the quality of the data collection process. Errors in data collection can lead to inaccurate stats and misleading conclusions. Different data providers might use different methods, leading to variations in the stats they provide for the same player.
• Focus on the individual: Player stats often focus on individual performance, neglecting the importance of teamwork and synergy. A player might have good individual stats but not contribute effectively to the team’s overall performance. A greedy player might hog the ball and get a good performance, but at the expense of his team’s overall performance or victory. Football is a team sport, and individual stats should be considered in the context of the team’s collective effort.
• Limitations with predictions: While player stats can be used to identify trends and make predictions about future performance, they are not always reliable predictors. Football is a complex and unpredictable game, and many factors like emotions, significance of the match (e.g. Champions league final), bitter derbies, playing old teams can influence a player’s performance from one game to the next.