Abstract
The objective of this study is to analyse the game-related statistics that differentiate winning and losing teams, according to the finale game scores in a men’s university basketball league. Samples were gathered from the archival data of the 2019–2020 regular season of the league. Sixteen game-related statistics were analysed: two- and three-point field-goals (both successful and unsuccessful), free-throws (both successful and unsuccessful), defensive and offensive rebounds, assists, steals, turnover, blocks, second-chance points, fast break points, fouls committed and received. The data were clustered into different game types based on the final outcome point differences: all games, balanced games (11 points and below) and unbalanced games (12 points and above). Discriminant function analysis was conducted to identify the performance indicators that classify winning and losing games. The results revealed that winning and losing in balanced games were discriminated by successful two-point field goals, unsuccessful two-point field goals, unsuccessful three-point field goals, successful free-throws, assists, steals, blocks, second-chance points, fast-break points, fouls committed, and fouls received. For unbalanced games, winning and losing were distinguished by successful two-point field goals, successful three-point field goals, successful free-throws, unsuccessful free-throws, defensive rebounds, blocks, fast-break points, and fouls received. In conclusion, offensive and defensive indices are critical to winning and losing in university-level basketball.
Highlights
Notational analysis is the process of recording, treatment, and diagnostics of events taking place in a competition (Drust, 2010)
The collected game statistics were normalized to ball possessions (BP) multiplied by 100
Field goal shooting is the most fundamental skill of the game as it shows the offensive quality of the winning team (Sampaio et al, 2006)
Summary
Notational analysis is the process of recording, treatment, and diagnostics of events taking place in a competition (Drust, 2010). Notational analysis plays an essential role in formulating strategies and optimizing training load (Sampaio et al, 2004; Lorenzo et al, 2010; Sampaio et al, 2015). Basketball-related statistics help improve the efficiency of players during the season (Sampaio et al, 2015) and predict final team rankings (Ziv et al, 2010). Basketball-related statistics provide useful information in winning and losing games. Ibáñez et al (2008) demonstrated that field goal attempts and defensive rebounds. Received: 10 September 2020 | Accepted after revision: 8 November 2020 | First published online: 1 September 2021
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
