Soccer Analytics
Master Data-Driven Soccer Analysis
Comprehensive soccer analytics covering xG models, passing networks, and tactical analysis
83
Tutorials4
Examples13
Datasets25
MetricsLearning Paths
Foundations of Soccer Analytics
6 TopicsFoundational concepts and core principles of soccer data science, including xG revolution and essential metrics
Getting Started
5 TopicsIntroduction to soccer analytics and fundamental concepts
Expected Goals (xG)
1 TopicsUnderstanding and calculating expected goals models
Passing and Possession Analytics
7 TopicsAdvanced analysis of passing metrics, possession value models, and ball progression frameworks
Defensive Analytics
8 TopicsComprehensive defensive metrics, pressing systems, ball recovery, and team defensive organization
Possession Analytics
5 TopicsPossession value, passing networks, and ball progression
Goalkeeper Analytics
5 TopicsSpecialized goalkeeper performance metrics including shot-stopping, distribution, and positioning analysis
Tactical Analysis
4 TopicsFormation analysis, pressing metrics, and spatial control
Player Evaluation
5 TopicsScouting, performance metrics, and player comparisons
Player Evaluation and Scouting
6 TopicsHolistic player evaluation frameworks, position-specific analysis, and recruitment analytics
Data Collection
5 TopicsAPIs, web scraping, and data sources for soccer
Team Tactics and Strategy
5 TopicsFormation analysis, tactical systems, pitch control, and strategic game planning
Set Pieces
4 TopicsCorner kicks, free kicks, and set piece analysis
Pressing and Transitions
4 TopicsHigh press, counter-press, and transition analytics
Transfer Market
4 TopicsPlayer valuation and transfer analytics
League Comparisons
4 TopicsComparing leagues and competitions
Quick Start Guide
Learn Basics
Start with fundamental statisticsAdvanced Metrics
Explore sport-specific analyticsPractice with Data
Use real datasets and examplesApply Knowledge
Build your own analytics projectsRecent Tutorials
Key Soccer Metrics
Expected Threat xT
Change in probability of scoring from moving the ball. Values all ball progression, not just shots. Variables: Based on grid of pitch divided into zones, each with historical scoring probability
\text{xT} = P(\text{Scoring from position})_{\text{end}} - P(\text{Scoring from position})_{\text{start}}
Expected Assists xA
Sum of xG values from chances created. Measures quality of chances created for teammates. Variables: Based on xG of shots resulting from player's passes/actions
\text{xA} = \sum(\text{xG of resulting shots})
Expected Goals Assisted xGBuildup
Total xG from possessions where player was involved (excluding assists and shots). Variables: Measures contribution to build-up play separate from direct goal involvement
\text{xGBuildup} = \sum(\text{xG of possessions involved in})
Aerial Duel Win Rate Aerial%
Percentage of aerial duels won. Important for defenders and target strikers. Variables: Aerial Duels Won = Headers won, Total Aerial Duels = All contested headers
\text{Aerial\%} = \frac{\text{Aerial Duels Won}}{\text{Total Aerial Duels}} \times 100
Expected Goals Against xGA
Sum of xG values from shots faced. Measures quality of chances conceded. Variables: xG values of all shots conceded by team/defender
\text{xGA} = \sum(\text{xG of shots conceded})
Interceptions Int
Number of opponent passes intercepted. Measures reading of the game. Variables: Counted when player intercepts an opponent pass attempt
\text{Int} = \text{Passes intercepted}
Tackles Won Tkl Won
Percentage of tackle attempts that win possession. Variables: Successful Tackles = Tackles winning the ball, Tackle Attempts = All tackle attempts
\text{Tkl Won} = \frac{\text{Successful Tackles}}{\text{Tackle Attempts}} \times 100
Progressive Carries ProgC
Ball carries that move at least 10 meters closer to the opponent goal. Variables: Excludes carries in own defensive third
\text{ProgC} = \text{Carries moving ball } \geq 10\text{m toward goal}
Successful Dribbles Drib%
Percentage of dribbles that successfully beat a defender. Variables: Successful Dribbles = Dribbles beating defender, Dribble Attempts = All take-on attempts
\text{Drib\%} = \frac{\text{Successful Dribbles}}{\text{Dribble Attempts}} \times 100
Expected Goals xG
Probability that a shot will result in a goal based on historical data. Most important advanced metric in soccer analytics. Variables: Shot location (distance, angle), shot type (foot, head), assist type, game state, and more
\text{xG} = P(\text{Goal}|\text{Shot Location}, \text{Type}, \text{Body Part}, ...)
Datasets & Resources
Ready to Master Soccer Analytics?
Start with the basics and work your way up to advanced machine learning applications.