Player Performance Index

Player Performance Index MCP Connector for Claude

A+

Calculate deterministic football player performance scores using weighted statistical components.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides a deterministic engine to calculate standardized football player performance scores. By normalizing raw statistics like goals, assists, and tackles, and applying role-specific weights, it generates a precise index. The engine uses calculate_player_index to provide a full breakdown of contributions and scale_by_efficiency to adjust scores to a standard per-90-minutes basis, ensuring fair comparison between players with different playing times.

footballsoccerperformancemetricsdata-analysis

4 tools expose this connector's capabilities to your AI agent.

calculate_player_index

Calculates the final performance index and provides a detailed breakdown

get_weight_configuration

g., Attacker, Midfielder, Defender) Retrieves the standard weight profiles for different player roles

scale_by_efficiency

Adjusts a raw accumulated score to account for the duration of play

validate_component_ranges

Checks if the provided statistics fall within the acceptable thresholds

See how to talk to your AI agent using Player Performance Index.

Calculate the performance index for a player with 2 goals, 1 assist, 3 key passes, 2 tackles, 1 interception, 0 errors, and 90 minutes played, using Attacker weights.

The calculated performance index is 15.45 with a breakdown of goals: 0.8, assists: 0.4, key passes: 0.3, tackles: 0.1, and interceptions: 0.05.

What are the standard weights for a Defender role?

The Defender profile weights are: goalWeight: 0.1, assistWeight: 0.1, keyPassWeight: 0.1, tackleWeight: 0.4, interceptionWeight: 0.3, and errorWeight: -0.2.

Adjust a raw score of 10.0 for a player who played only 45 minutes.

The efficiency-adjusted score for 45 minutes played is 20.0.

The score is calculated by normalizing raw statistics, applying weights defined by player roles, and then scaling the result based on minutes played using `scale_by_efficiency`.

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