What are Kama Player Labels and Why Are They The Future of Player Analysis

As football continues to grow and evolve technologically, Kama stays one step ahead to support football professionals in elevating their game to new heights. To highlight our innovative efforts, we recently unveiled one of our newest solutions, Kama Team Labels. Powered by advanced statistical models and machine learning, Kama Team Labels summarize the most impactful aspects of each team's game, allowing for the instantaneous and intuitive analysis of a team's statistics.

The outputs are segmented into 3 unique sections (Strengths, Weaknesses, Style of Play) that reflect the overall performance of a team while highlighting their strong points, shortcomings and overall game style. The use of Kama Team Labels allows users to quickly navigate the complex football ecosystem and facilitate a comprehensive, rapid, and intuitive analysis of a team. Despite all of its perks, the feature was limited to teams and served more as a general overview rather than an extensive report.

To ensure that users receive the most accurate and detailed information about a football team’s capabilities, we are now excited to present the newest addition to the Kama platform - Kama Player Labels. An extension of the Team Labels, Kama player labels zoom in on a player’s strengths and weaknesses, making it more intuitive for users to analyze the true value a player brings on the pitch.

Kama Player Labels are categorized into 3 unique sections: Game Features, Strengths and Weaknesses.

1. Game Features

Through Machine Learning algorithms, players are categorized based on specific playing characteristics for their respective roles. The goal is to provide a precise and objective description of the player's on-field abilities, based on their contribution to the team, evaluated across a substantial group of game statistics. Each group is displayed with a relative percentage, indicating how well the player's characteristics align with the specified archetype.

For the specific role, the algorithm identifies the following archetypes:

• Offensive phase enhancer: Striker who makes 1vs1 skills his specialty, able to dribble past defenders and turn the action from defensive to offensive through effective carries.
• Target offensive player: Offensive reference who is not necessarily a striker, physically strong and who plays for the team.
• Central scorer: Striker who prefers patrolling the central area of the attack, seeking to finish the play.
• Breakthrough offensive player: Player who positions himself in the offensive zone but makes breakingthrough plays his specialty.
• Between the lines target: Positional offensive player, dominant on the high ball, with great physical presence. Tends to position himself as a reference in the central zone.
• Reliable offensive player: Offensive player who does not excel or flaw in any precise characteristic of the game, a balanced player.
• Versatile offensive player: Multipurpose offensive player, able to cover multiple roles reliably, physically strong and dangerous when carrying. Not always effective in scoring.
• Offensive chance creator: Clever offensive player whose priority is to create through dangerous passes and crosses, rather than finishing.
• Dynamic scorer: Forward who likes to roam across the entire offensive front, dangerous with the ball at his feet, and a threat in the goal area.

2. Strengths

Strength points are divided into offensive and defensive, then evaluated on three distinct levels, identified as follows:

• Top in the best 5 European competitions: indicates that the player is in the top 5th percentile among all players in teams belonging to the top 5 European leagues.
• Top in the league: indicates that the player is in the top 5th percentile among players in their respective league.
• Strong in the league: indicates that the player is between the 85th and 95th percentile among players in their respective league. If the player is both Top in the best 5 competitions and Top in their own league, only the European level will be shown, implying the one related to their own league.

We consider the Premier League, Serie A, Bundesliga, Ligue 1 and LaLiga to be the Top 5 European leagues. It is also important to mention that all labels are calculated by analyzing data from the last 1000 minutes played.

3. Weaknesses

Weakness points are divided into offensive and defensive, then evaluated on three distinct levels, identified as follows:

• Worse in the best 5 European competitions: indicates that the player is in the worst 5th percentile among all players in teams belonging to the top 5 European leagues.
• Worse in the league: indicates that the player is in the worst 5th percentile among players in their respective league.
• Weak in the league: indicates that the player is between the 5th and 15th percentile among players in their respective league.

Same as the strength labels, If the player is both Top in the best 5 competitions and Top in their own league, only the European level will be shown, implying the one related to their own league.