NextMatch Yuwei Liu

Win your next match!

• Identify variables that matter in terms of winning • Offer actionable insights for match strategy plan

Problem: Use data to impact soccer match outcome

Solution: NextMatch

“Many organizations spend considerable sums on collecting data, but lack the capability to … analyze the data using machine learning.”– Tony Strudwick, Head of Athletic Development, Manchester United FC

“(By doing simple correlation, one finds no single stats matters for winning), the only stats that matters is winning”– Jo Clubb, Lead Sport Scientist, Chelsea FC

Demo of the website: nextmatch.club

Scraped 3 years of match stats for each team in the Spanish Soccer League from whoscored.com

Data and Algorithm

Outcome of Team A’s match

Features of team A

Features of team A’s opponent

1: win / 0: not win Passes, Shots, … Passes_OP, Shots_OP, …

Step Algorithm Advantage

1. Feature Selection

Random Forest Dealing with large No. of features while maintaining interpretability

2. Classification Logistic regression using features selected above

Simple; Easy interpretation; Sign of coefficients

A different set of models for each team

Model Performance

Model performs well on most teams

Training: 12/13-13/14 season, 76 matches / team; Testing: 14/15 season, 18 matches / team

Model Performance

Matches of teams that change squad a lot in a short period are less predictable

Training: 12/13-13/14 season, 76 matches / team; Testing: 14/15 season, 18 matches / team

Use Case – for the team ValenciaValencia Sevilla

Round 1 1 1

Go to NextMatchBefore Round 2

Use Case – for the team Valencia

Match Valencia Sevilla

Round 2 3 1

Recommendations Valencia “followed”

Yuwei Liu