Identifying group contributions in NBA lineups with spectral analysis

TL;DR

This paper introduces a spectral analysis method to quantify and decompose team success contributions of individual players and groups in NBA lineups, providing a clear understanding of lineup effectiveness.

Contribution

The paper applies spectral analysis from algebraic signal processing to NBA data, enabling orthogonal decomposition of lineup contributions by group size.

Findings

Decomposes team success into contributions of players and groups

Separates contributions of different group sizes orthogonally

Provides a practical tool for analyzing lineup effectiveness

Abstract

We address the question of how to quantify the contributions of groups of players to team success. Our approach is based on spectral analysis, a technique from algebraic signal processing, which has several appealing features. First, our analysis decomposes the team success signal into components that are naturally understood as the contributions of player groups of a given size: individuals, pairs, triples, fours, and full five-player lineups. Secondly, the decomposition is orthogonal so that contributions of a player group can be thought of as pure: Contributions attributed to a group of three, for example, have been separated from the lower-order contributions of constituent pairs and individuals. We present detailed a spectral analysis using NBA play-by-play data and show how this can be a practical tool in understanding lineup composition and utilization.