Decision-Making Skills in Youth Basketball Players: Diagnostic and External Validation of a Video-Based Assessment

Abstract

Decision-making is a central skill of basketball players intending to excel individually and contribute to their teams’ success. The assessment of such skills is particularly challenging in complex team sports. To address this challenge, this study aimed to conceptualize a reliable and valid video-based decision-making assessment in youth basketball. The study sample comprised youth basketball players of the German U16 national team (n = 17; MAge = 16.01 ± 0.25 years) and students of a sports class (n = 17; MAge = 15.73 ± 0.35 years). Diagnostic validity was tested by determination of the performance levels according to response accuracy as well as response time in the assessment. External validity was examined by investigation of the correlation between the diagnostic results of the elite athletes and their real game performance data associated with passing skills. Logistic regression analysis revealed that the diagnostic results discriminate between performance levels (χ2(2) = 20.39, p < 0.001, Nagelkerke’s R2 = 0.60). Multiple regression analysis demonstrated a positive relationship between the diagnostic results and assists (F(2,10) = 4.82, p < 0.05; R2 = 0.49) as well as turnovers per game (F(2,10) = 5.23, p < 0.05; R2 = 0.51). However, no relationship was detected regarding the assist-turnover ratio. Further, response time discriminated within the elite athletes’ performance data but not between performance levels while for response accuracy the opposite is the case. The results confirm the diagnostic and external validity of the assessment and indicate its applicability to investigate decision-making skills in youth basketball.

Basketball training frequency is associated with executive functions in boys aged 6 to 8 years

“…In accordance with the present results, previous studies have demonstrated that weekly open skills training had no significant impact on children's inhibitory control and working memory (Ishihara et al, 2018), while prolonged training of the same type five times a week improved their cognitive flexibility, inhibitory control, and working memory (Hillman et al, 2014). Basketball is a cognitively engaging exercise that requires the understanding of rules, peer competition, and the memory of technical movements, all of which require the participation of EFs (Rösch et al, 2021). It can be concluded that increasing the frequency of a cognitively engaging exercise has a positive effect on children's EFs.…”

[Retracted] CNN‐LSTM Hybrid Model for Kinematic Feature Analysis and Parabolic Radian Prediction in Basketball Videos

“…LSTM can effectively solve this problem by capturing the dependencies of long time series more easily than RNN. However, it has been experimentally observed that in some cases, especially in very long sequences, the LSTM does not always remember long interdependencies and correlations correctly [13]. is leads to a decrease in the performance of the neural network with the passage of time, which leads to the so-called longrange dependence problem.…”

“…CNN is an artificial neural network that has dominated in various computer vision tasks [13,22,23]. e key feature of the convolution operation is weight sharing: the kernel is shared over all image locations.…”

“…e study in [12] aims to achieve action recognition by doing shape matching of key video frames extracted from the video with the saved original action. e study in [13] computes the optical flow field of a target in a video using fuzzy optical flow features and achieves online action recognition by template matching. e study in [14] proposes expressing the action recognition of a target by features of key point motion history.…”

The Influence of Acute Sprint Interval Training on the Cognitive Performance of Male Basketball Players: An Investigation of Expertise-Related Differences

“…Although the above-mentioned evidence strongly suggests that cognitive abilities are crucial in team sports such as basketball, the evidence concerning expertise-related differences (e.g., amateur athlete vs. elite athlete) is not exhaustive, as most of the available studies compared basketball athletes to non-athletes [ 13 , 14 ]. Thus, further research is necessary to reach a more comprehensive and nuanced understanding of the effect of the sport-specific expertise level on cognitive performance [ 1 , 15 , 16 ].…”