Project · Chart Gallery

Visualizing Player
Performance Data

Eight analytical views generated from FutrixMetrics' rating and clustering pipeline — covering overall metrics, positional radar profiles, role clustering distributions, and Gaussian mixture model outputs.

Radar Charts Rating Views GMM Outputs Cluster Analysis
8 Chart Types
4 Analysis Dimensions
GMM Gaussian Mixture Model
Multi-Position Positional Coverage
Rating & Radar

Overall metrics and positional profiling

The rating pipeline scores each player across key performance dimensions. Radar charts break these scores into positional profiles, making it easy to compare tactical fit across roles.

Chart 01

Overall Metric Chart

Aggregated performance scores across all measured dimensions — the starting point for player evaluation.

Scoring Aggregation
Overall metric chart showing aggregated player performance scores
Chart 02

Position Radar Chart

Multi-axis radar view that maps player attributes by position — revealing strengths and gaps in positional context.

Radar Positional
Position radar chart mapping player attributes by role
Ranking & Comparison

Top performers and position-based scoring

Identify the highest-rated players across the dataset and compare how position-specific metrics rank against peers. These views feed directly into scouting shortlists and recruitment decisions.

Chart 03

Top Players Chart

Ranked view of the highest-scoring players — a direct output from the rating model used for rapid shortlisting.

Ranking Top N
Top players chart showing highest-rated performers
Chart 04

Position Rating Chart

Comparative rating distribution across positions — showing how players score within their own positional group.

Distribution By Position
Position rating chart comparing scores within positional groups
Cluster Analysis

Role clustering and player segmentation

The clustering pipeline groups players by statistical similarity rather than nominal position. This reveals hidden role archetypes — from deep-lying playmakers to pressing forwards — that traditional position labels miss.

Cluster stacked chart showing player role distribution
Chart 05

Cluster Stacked Chart

Stacked distribution of player role clusters — showing how players segment across data-driven archetypes rather than traditional positions.

GMM Model Output

Gaussian mixture model visualizations

The GMM layer adds probabilistic depth to the clustering pipeline. Histogram, summary, and scatter views show how the model separates player populations, assigns cluster membership probabilities, and maps multi-dimensional performance space.

GMM histogram showing player distribution across clusters
Chart 06

GMM Histogram

Distribution of players across GMM-assigned clusters — visualizing how the model separates the population.

GMM summary chart showing cluster characteristics
Chart 07

GMM Summary

Cluster-level summary statistics — mean values, variance, and membership size for each Gaussian component.

GMM scatter chart showing multi-dimensional cluster mapping
Chart 08

GMM Scatter

Multi-dimensional scatter plot mapping player positions in reduced feature space — each point colored by GMM cluster assignment with probabilistic boundaries.

Explore the full analytics pipeline

These charts are outputs from the FutrixMetrics rating and clustering model. Dive deeper into the methodology or try the platform yourself.