The Ultimate Guide to Soccer Analytics
Master football analytics with R and Python. From traditional statistics to cutting-edge expected goals (xG) and tracking data, learn the exact skills used by professional clubs, scouts, and analysts worldwide.
# Get free StatsBomb match data
from mplsoccer import Pitch
import pandas as pd
from statsbombpy import sb
# World Cup 2022 Final: Argentina vs France
matches = sb.matches(competition_id=43, season_id=106)
events = sb.events(match_id=3869685)
# Calculate xG by team
shots = events[events['type'] == 'Shot']
xg_summary = shots.groupby('team').agg({
'shot_statsbomb_xg': 'sum',
'shot_outcome': lambda x: (x == 'Goal').sum()
})
print(xg_summary)
# Argentina: 2.77 xG, 3 Goals
# France: 2.44 xG, 3 Goals
Why Choose This Textbook
Everything you need to master soccer analytics
Dual Language Coverage
Side-by-side R & Python code for every concept. Toggle between languages with a single click. Learn best practices for each language.
Expected Goals (xG) Era Analytics
Modern tracking data examples, xG, xA, xGChain, xGBuildup. Pressing & possession analytics using industry-standard metrics.
Career-Ready Skills
Industry-standard methods used by professional clubs. Portfolio project ideas and dedicated career guidance chapter.
Machine Learning
Player similarity models, match outcome prediction, recruitment optimization. From basic regression to neural networks.
Interactive Visualizations
Pitch plots with mplsoccer, pass networks & heat maps, shot maps, touch maps, and radar charts for player comparison.
Global Coverage
Premier League, La Liga, Serie A, Bundesliga, Ligue 1, MLS, FIFA World Cup, Champions League, and women's football analytics.
Your Learning Journey
A structured path from beginner to expert
Foundations
R/Python basics, data wrangling, accessing soccer data sources. Set up your environment and build your first visualizations.
Core Analytics
Traditional stats, xG models, passing analytics, defensive metrics. Master the fundamental metrics used in professional analysis.
Advanced Methods
Tracking data, ML models, custom metrics, pitch control. Build sophisticated models like the pros.
Applied Topics
Positional analysis, scouting, tactics, business analytics. Apply your skills to real-world scenarios.
Who Is This For?
Whether you're a fan or professional, there's something for you
Aspiring Analysts
Launch your career in football analytics
Fantasy Players
Gain an edge with data-driven decisions
Students
Apply data science to sports
Journalists
Tell compelling data stories
Scouts
Find hidden gems with analytics
Passionate Fans
Understand the game deeper
Ready to Master Soccer Analytics?
Join thousands learning to analyze the beautiful game with data.
Start Learning Now