Offensive Patterns and Performance Analysis in One-Possession Scenarios During the Last Minute and Overtime in the EuroLeague
Source abstract
Abstract
In elite basketball, closely contested games are often decided in the last minute, where a single possession can significantly alter the outcome. The objective of this study was to analyze the offensive patterns and effectiveness of successful play sequences executed during the last minute and overtime periods of the 2022–2023 EuroLeague men’s basketball season. Specifically, we examined how offensive strategies varied based on score conditions and team status (winning, losing, or tied) in games with a score difference of three points or fewer, representing a maximum one-possession margin. The sample consisted of 709 technical–tactical actions performed in one-possession games during the last minute and overtime periods of the men’s EuroLeague 2022–2023 season. An observational methodology was employed using the LINCE PLUS software with a purpose-designed observational instrument. Descriptive analyses and chi-square (χ2) tests were conducted using SPSS 25, and T-Pattern analysis was performed with Theme 6 software. Statistical significance was set at p < 0.05. The results showed that teams leading at the start of the possession executed a higher number of successful actions, primarily through free throws drawn from fouls committed by the opposing team. Additionally, plays involving few or no passes, executed within the first 17 s of possession, and completed by point guards or centers, were associated with higher success rates. While less frequent, fast breaks proved to be more effective than set offenses. Furthermore, the study highlights the role of elite playmakers in late-game situations, as their ability to read defenses and create scoring opportunities plays a crucial role in determining offensive success. The practical implications of this study can assist coaches in optimizing offensive strategies during high-pressure moments in elite men’s basketball by refining late-game decision-making and tactical planning.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sports Analytics and Performance · Sports Performance and Training · Software Engineering Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Observational Research Group, Faculty of Education and Sport, University of Vigo, 36005 Pontevedra, Spain
Education, Physical Activity and Health Research Group (Gies10-DE3), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36208 Vigo, Spain
Funding
Evolución del software LINCE PLUS y desarrollo de la aplicación móvil para la optimización del deporte y la actividad física beneficiosa para la salud · Axudas Predoutorais para a formación de Doutoras/es 2022, Universidade de Vigo
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