Beyond Traditional Metrics: A Systematic Review of Spatial and Spatiotemporal Indicators in 5-on-5 Basketball

Basketball performance analysis has traditionally relied on event-based statistics and box-score-derived metrics. Although these measures describe performance outcomes, they provide limited information about how actions are shaped by player location, movement, and interaction during play. With the growing availability of court-referenced player and ball location data, spatial and spatiotemporal indicators have become increasingly common for describing game behavior in basketball. For the purposes of this review, spatial indicators were defined as location-based measures captured at a given moment, such as shot location, defender distance, or team spacing. Spatiotemporal indicators were defined as measures that capture movement or changes in spatial configuration over time, such as dyadic coordination, team expansion, or changes in possession value. This systematic review examined how these indicators have been operationalized and applied, and how their outputs have been interpreted in relation to tactical performance. This systematic review was conducted in accordance with the PRISMA guidelines. Searches were conducted in PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar for studies published through 15 September 2025. Studies were eligible if they examined standard, regulation 5-on-5 basketball, used court-referenced player and/or ball location data during match play, and derived spatial or spatiotemporal indicators relevant to tactical, technical-tactical, or game-performance questions. Reporting completeness and transparency were appraised using a STROBE-based framework for empirical/observational studies and an adapted TRIPOD-informed checklist for modeling/analytics studies. A total of 759 records were identified, of which 16 studies met the inclusion criteria. The included studies addressed offensive, defensive, and combined offensive-defensive contexts. Five studies used a state-based measurement approach, eight used a sequence-based approach, and three used both. Individual/local spatial indicators most commonly included shot location, distance to the basket, defender distance, shot angle, and shot-trajectory factors. Interactional indicators included dyadic coupling, attacker-defender distance, passer-receiver relations, and secondary-assist-related measures. Collective indicators included team spatial center, stretch index, court-area occupation, team width, and centroid movement. Defensive-impact indicators included defensive shot frequency and shot-efficiency effects, whereas model-derived and complexity indicators included expected possession value, player gravity, and intrinsic dimension. Spatial and spatiotemporal indicators extend basketball performance analysis beyond traditional outcome-based metrics by revealing where players were located, how they interacted spatially, and how team structure changed during possessions. However, they should not be interpreted as direct measures of tactical effectiveness. Their interpretation should be anchored in possession phase, shot or pass event, defender proximity, offensive or defensive context, and whether the indicator was derived from a single game state or a sequence of play.