Association Between Efficiency of Movement Patterns and Basketball Performance: An Exploratory Study

Basketball is a sport that requires players to execute a variety of multidirectional movements that have technically-skilled components of both offense and defense. While research has explored the relationships between a) strength and conditioning measures and basketball performance and b) strength and conditioning measures and measurements of movement efficiency, at this time we are unaware of any research that has investigated if movement efficiency and basketball performance are inter-related. PURPOSE: To explore the association between efficiency of movement and basketball performance. METHODS: Pre-season, participants (n=17) were recruited from a men’s and women’s NCAA Division 1 basketball team. Spatio-temporal movement parameters and their inefficiencies were analyzed using the OptoGait. After a controlled warm-up, participants were asked to complete a 30-second treadmill walk and run, sprint 5 meters, and perform a single and double leg vertical and broad jump. Movement pattern efficiency for gait-based parameters was operationally defined as variance in lower limb movement (e.g., variance in gait speed, single leg support time), with greater variance being considered as inefficient. For jumping movements, inefficiency of movement was defined as larger landing areas and jump points. Basketball statistics were downloaded post-season and each player’s basketball statistics were normalized to 30 minutes. Zero-order correlations were used to identify the relationship between basketball statistics and movement inefficiencies. RESULTS: While there were many (178) significant relationships present, the direction of the relationships was as expected with larger inefficiencies in movement being associated with worse basketball performance. Variances in sprint acceleration were negatively associated with most basketball statistics, with some of the largest relationships being field goal percent (-0.647), free throw attempt (-0.912), and total rebounds (-0.844). CONCLUSION: Taken together, the findings suggest that players who move inefficiently during running and while jumping tend to perform worse when they are playing basketball. Although this study did not identify how these inefficiencies impacted player performance, the results from this exploratory study suggest that investigation into this area is warranted. Our findings provide evidence that strength and conditioning researchers should also seek to understand whether movement efficiencies influence performance in other sports and also further investigate these relationships in basketball players with larger sample sizes

Sex Moderates the Fitness Tests - Performance Index Relationship in Collegiate Basketball: A Case Study

Performance indicators are used widely in sports, including basketball. Those total performance metrics are mathematical models that are used to determine the “best” athlete per game/week/season. Players with higher metrics get recruited more and/or get offered better contracts. During offseason, strength and conditioning coaches (SCCs) perform tests to determine the fitness levels of their players. Although those scores differ by sex, the fitness levels are associated with in-season sport performance and, therefore, performance indices. More insight in the fitness tests - performance index relationship in the collegiate basketball and the differential effects by sex would be valuable for all stakeholders (e.g., SCCs, sport coaches, sport agents). In the US, the Player Efficiency Rating (PER) and Efficiency (EFF) are the most commonly used basketball performance indices. PURPOSE: To investigate a) correlation between the uPER and EFF by sex and b) which fitness test most strongly correlates each index by sex. METHODS: Ten male and eight female basketball players (n = 18) from the same college participated. Several fitness tests (full court sprint, bench press, power clean, vertical jump, standing broad jump, and T drill) were performed in the off-season. Performance data, which were collected throughout the following season, were used to calculated unadjusted PER (uPER; equation not shown for space) and EFF (PTS + REB + AST + STL + BLK − Missed FG − Missed FT - TO) / GP). To examine the characteristics of fitness test distributions by sex, the means and standard deviations were generated for each sex. Pearson correlations were estimated as indicators for the relationship between the performance indices and also the relationships between each of the fitness tests and the performance indices by sex. RESULTS: Our results showed lower means and less variability of the fitness tests scores in women than men. The correlation between uPER and EFF in men was moderate (r = .359) and strong in women (r = .662). No strong correlation was found in men between any fitness test and EFF, while full court sprint was strongly correlated with uPER (r = .738). In women, strong correlations were detected between a) T drill and EFF (r = .574) and b) foul court sprint (r = .610), vertical jump (r = .662), and T drill (r = .659) and uPER. No statistical inferences were made due to the nature of the study. CONCLUSION: Our outcomes suggest that uPER and EFF reflect different amounts of information based on sex. Practical implications include that a) foul court drill scores may predict uPER more accurately in both men and women and b) T drill scores may predict both EFF and uPER more precisely in women. Future, larger-scale studies should replicate in other settings with larger samples. Limitations may include small sample size