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

Suggested data model for call center analytics

Plugins

Implementation
Kit

The following resources will enable you to design your dashboard and data model with sample data and then apply it to your own data. Note that you will need to have a previously installed version of Sisense (you can use the free trial version if you’re not a customer).

Sample data and dashboard examples (direct download)

Documentation