Player Performance

High Level Design

Overview

Data analytics in professional sports has grown exponentially in the last decade. Instead of making decisions to draft or trade on a coaches personal opinion, teams are looking to data for the answers. Professional Soccer/Football is no exception. The need for an increasing edge over your opponents is only increasing the need for accurate player monitoring and performance tracking.

Goals

Analyze player performance

• Better decision making when trading players
• Understand when a player is ready to be substituted during a match
• Gain deeper insight into individual player KPIs

Objectives

Track Performance KPIs:

• Match Attendance
• Passing Accuracy
• Goals
• Successful Shots on Target Rate
• Successful Tackle Rate

KPI Architecture

Objective	KPI’s	Measures	Data source
Track Performance KPIs	Match Attendance	Sum(Appearance) / Count(GameID) *All Games	Fact_Game
	Passing Accuracy	Sum(SuccessfulPasses) / Sum(Passes)	Fact_Game
	Goals	Sum (Goals)	Fact_Game
	Successful Shots on Target Rate	Sum(ShotsonTarget) / Sum(Shots)	Fact_Game
	Successful Tackle Rate	Sum(SuccssefulTackles) / Sum(Tackles)	Fact_Game

Entities Relationship Diagram

Plugins

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