Who needs a referee? How incorrect basketball actions are automatically detected by basketball players' brain.
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ABSTRACT:
SUBMITTER: Proverbio AM
PROVIDER: S-EPMC3504931 | biostudies-other | 2012
REPOSITORIES: biostudies-other
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Project description:Reinforcement learning in complex natural environments is a challenging task because the agent should generalize from the outcomes of actions taken in one state of the world to future actions in different states of the world. The extent to which human experts find the proper level of generalization is unclear. Here we show, using the sequences of field goal attempts made by professional basketball players, that the outcome of even a single field goal attempt has a considerable effect on the rate of subsequent 3 point shot attempts, in line with standard models of reinforcement learning. However, this change in behaviour is associated with negative correlations between the outcomes of successive field goal attempts. These results indicate that despite years of experience and high motivation, professional players overgeneralize from the outcomes of their most recent actions, which leads to decreased performance.
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Project description:BACKGROUND:The aim of this study is to describe the peak match demands and compare them with average demands in basketball players, from an external load point of view, using different time windows. Another objective is to determine whether there are differences between positions and to provide an approach for practical applications. METHODS:During this observational study, each player wore a micro technology device. We collected data from 12 male basketball players (mean ± SD: age 17.56 ± 0.67 years, height 196.17 ± 6.71 cm, body mass 90.83 ± 11.16 kg) during eight games. We analyzed intervals for different time windows using rolling averages (ROLL) to determine the peak match demands for Player Load. A separate one-way analysis of variance (ANOVA) was used to identify statistically significant differences between playing positions across different intense periods. RESULTS:Separate one-way ANOVAs revealed statistically significant differences between 1 min, 5 min, 10 min, and full game periods for Player Load, F (3,168) = 231.80, ?p2 = 0.76, large, p < 0.001. It is worth noting that guards produced a statistically significantly higher Player Load in 5 min (p < 0.01, ?p2 = -0.69, moderate), 10 min (p < 0.001, ?p2 = -0.90, moderate), and full game (p < 0.001, ?p2 = -0.96, moderate) periods than forwards. CONCLUSIONS:The main finding is that there are significant differences between the most intense moments of a game and the average demands. This means that understanding game demands using averages drastically underestimates the peak demands of the game. This approach helps coaches and fitness coaches to prepare athletes for the most demanding periods of the game and present potential practical applications that could be implemented during training and rehabilitation sessions.
| S-EPMC7177956 | biostudies-literature
Project description:A large portion of previous sport talent development research has been conducted using Western countries study subjects such as Canadian, Swedish, Spanish, British, or American athletes. However, the factors that affect oriental culture athletes remain an unexplored field. The aims of this investigation were to consolidate the exploration of the pilot study that studied the key factors for Chinese elite basketball players' careers and understand what facts have helped them to achieve the highest sportive level through qualitative research. The pathway to excellence of 11 Chinese elite basketball players were analyzed through a semi-structured interview with different categories such as social context, sport context, tactical factors, or anthropometric factors. Results showed that cultural factors, family tradition, academic studies, coaches, mental strength, training structuration, and international competitions had a great effect and influence in the talent development of Chinese basketball players.
| S-EPMC7400287 | biostudies-literature
Project description:ImportanceThere is a paucity of data detailing cardiac remodeling in female athletes compared with male athletes. The lack of reference cardiac data for elite female basketball players or female athletes of similar size makes it difficult to differentiate athletic remodeling from potential underlying cardiac disorders in this population of athletes.ObjectiveTo assess cardiac structure and function in elite female basketball players.Design, setting, and participantsThis cross-sectional echocardiographic study included 140 Women's National Basketball Association (WNBA) athletes on active rosters for the 2017 season. The WNBA mandates annual preseason stress echocardiograms for each athlete. The WNBA has partnered with Columbia University to annually perform a review of these studies. Data analysis was performed from June 7, 2017, to October 5, 2017.Main outcomes and measuresEchocardiographic variables included left ventricular (LV) dimensions, wall thickness, mass, prevalence of LV hypertrophy, aortic dimensions, right ventricular (RV) dimension, and right and left atrial size. Linear regression was used to assess the associations between cardiac structure and function with body size quantified as body surface area (BSA) in the primary analysis.ResultsA total of 140 female athletes (mean [SD] age, 26.8 [3.9] years; 105 [75.0%] African American) participated in the study. Mean (SD) athlete height was 183.4 (9.0) cm, and mean (SD) BSA was 2.02 (0.18) m2. Compared with guideline-defined normal values, LV enlargement was present in 36 athletes (26.0%) and 57 athletes (42.2%) had RV enlargement. There was a linear correlation between LV and RV cavity sizes and BSA extending to the uppermost biometrics (LV cavity size: r, 0.48; RV cavity size: r, 0.32; P < .001 for both). Maximal left ventricular wall thickness (LVWT) ranged from 0.6 to 1.4 cm, with 78 athletes (55.7%) having LVWT of 1.0 cm or greater and only 1 athlete (0.7%) having LVWT greater than 1.3 cm. Twenty-three athletes (16.4%) met the criteria for left ventricular hypertrophy (LVH) (>95 g/m2). Eccentric LVH was present in 16 athletes (69.6%), concentric LVH in 7 athletes (30.4%), and concentric remodeling in 27 athletes (19.3%). Mean aortic root diameter was 3.1 cm (95% CI, 3.0-3.2). Only 2 athletes (1.4%) had guideline-defined aortic enlargement compared with a range of 18% to 42% for left and right ventricular and atrial enlargement.Conclusions and relevanceIn this study, increased cardiac dimensions were frequently observed in WNBA athletes. Both BSA and physiologic remodeling affected cardiac morphologic findings. This study may provide a framework to define the range of athletic cardiac remodeling exhibited by elite female basketball players.
| S-EPMC7315385 | biostudies-literature
Project description: Not available
| S-EPMC10593457 | biostudies-literature
Project description:ObjectiveProfessional Basketball players are at high risk of Achilles tendon rupture. Despite this, there remains limited research into the factors affecting rehabilitation and the long term outcomes of these players. Our aim is to quantify the effect of a player's Achilles tendon rupture on their post-injury performance, and also to explore for correlations between their recovery timeline and pre-injury characteristics. Creation of an injury timeline of past incidents will allow injured players to better track their progress and also inform them about the probable impact on their careers.HypothesisPlayers with Achilles tendon rupture injury will exhibit decreased performance compared to their pre-injury self and their non-injured peers after recovery.MethodsProfessional basketball players who sustained a unilateral Achilles tendon rupture from 1992 to 2016 were collected. 12 players met our inclusion criteria and their Player Efficiency Ratings (PER) were obtained as primary outcome measures; matched controls were chosen based on the PER, Age and playing position. The players' index season PER was compared against the PER during the 10 games immediately following the players' return and the PER of their post-injury peak performing season. The same data analysis was performed against their control group. To investigate the factors affecting the recovery and long-term consequences of their injury, we correlated the variables of Age, BMI, Time of Injury and pre-injury PER with the player's time to return to play and their post-injury PER.Results2 out of 12 players failed to return to playing in the elite professional league following an Achilles Tendon Rupture, others returned after a mean recovery time of 10 months. When compared to players' index PER, the mean PER reduction during the 10 games immediately following the players' return was 7.15 (P < .000). Players on average took 1.8 seasons to reach their post-injury peak performance, with only 1 player returning to his pre-injury performance. Others suffered a mean PER reduction of 3.5 (P = .004) when compared to their index PER and 5.4 (P = .045) against their matched controls.ConclusionAchilles tendon rupture can be a career-ending injury for professional basketball players. They are expected to miss 10 months for rehabilitation and reach their post-injury peak performance level at the 2nd season back. The post-injury peak performance is significantly worse than the pre-injury level, but is similar to matched non-injured players.
| S-EPMC7327851 | biostudies-literature
Project description:Background: The interpretation of young athletes' performance during pubertal years is important to support coaches' decisions, as performance may be erroneously interpreted due to the misalignment between chronological age (CA), biological age (BA) and sport age (SA). Aim: Using a Bayesian multilevel approach, the variation in longitudinal changes in performance was examined considering the influence of CA, BA (age at menarche), SA, body size, and exposure to training among female basketball players. Method: The study had a mixed-longitudinal design. Thirty eight female basketball players (aged 13.38 ± 1.25 years at baseline) were measured three times per season. CA, BA and SA were obtained. Anthropometric and functional measures: countermovement jump, Line drill (LD), Yo-Yo (Yo-Yo IR1). Based on the sum of the z-scores, an index of overall performance was estimated. The effects of training on longitudinal changes in performance were modeled. Results: A decrease in the rate of improvements was apparent at about 14 years of age. When aligned for BA, the slowing of the rate of improvements is apparent about 2 years after menarche for LD. For countermovement jump longitudinal changes, when performance was aligned for BA improvements became linear. For Yo-Yo IR1 and performance index, both indicators showed a linear trend of improvement when aligned for CA and BA, separately. Older players showed higher rates of improvement for Yo-Yo IR1 and performance index from pre-season to end-season. When considering performance changes aligned for BA it was apparent an improvement of performance as players became biologically mature. Conclusions and Implications: The alignment of CA with BA and SA provides important information for coaches. Human growth follows a genetically determined pattern, despite variation in both tempo and timing. When the effects of maturation reach their end, all the girls went through the same process. Hence, there is no need to artificially manipulate youth competitions in order to accelerate gains that sooner or later reach their peak and tend to flat their improvement curve.
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Project description:The study aim was to assess the reliability to active trunk movements measurement in four sitting positions in wheelchair basketball players and to check their trunk movements in these positions. Eighteen volunteer wheelchair basketball athletes, with a minimum of five years' training experience, were asked to perform the maximum range of active trunk movement in three planes in four sitting positions (in a sports wheelchair with straps, without straps, on a table with feet on the floor, on a table without foot support). The range of movement was measured by the Kinect for Windows V2 sensor twice (with one-week interval). To assess the reliability, different statistical methods were used for each movement: significance of differences between the results (p-value), interclass correlation coefficient (ICC) and minimal detectable change (MDC). The limits of agreement analysis (LOA) were calculated. Differences between trunk movements in four positions were checked by the MANOVA (Wilk's Lambda and ETA2 were calculated if data were normally distributed). The significance level was set at ? < .05. Friedman ANOVA and non-parametric Wilcoxon test with the Bonferroni correction were applied when data were not normally distributed. The significance level after Bonferroni correction was set at ? < .013 (? = p/k, where p = .05, k-number of positions = 4). The measurement of active trunk movement in each plane was reliable (p > .05, no differences between the results, "very good"ICC, between .96-.99). In the position with straps, the trunk movement was significantly bigger than in other positions (p < .05), except for the position without straps (p > .05). The Kinect for Windows V2 sensor measured active trunk movement in a reliable manner and it can be recommended as a reliable tool for measuring trunk function. Utilizing straps by wheelchair basketball players increases their trunk movement.
| S-EPMC6872154 | biostudies-literature
Project description:This study aimed to (1) use the clustering method to build a classification model based on the play-type data of basketball players, to classify native and foreign players into different offensive roles; (2) use the clustered offensive role model to investigate how different offensive roles influence team performance. The sample was drawn from 20 teams spanning five seasons (2017-2021) in the Chinese Basketball Association, comprising 823 native and 228 foreign players. The clustering results obtained fourteen offensive roles for native players and five for foreign players. Subsequent analyses revealed that the offensive roles of two native player clusters, namely N6 Spot-up Wings who Attack (OR = 3.281, p < 0.05) and N13 Bigs who Cut to the Rim (OR = 4.272, p < 0.05), significantly influenced team performance. Conversely, no significant impact was observed for foreign players. The findings of this study offer novel insights into player dynamics and offer coaches a fresh perspective on team composition.
| S-EPMC10514490 | biostudies-literature
Project description:Study Objectives: Microsleep episodes (MSEs) are short fragments of sleep (1-15 s) that can cause dangerous situations with potentially fatal outcomes. In the diagnostic sleep-wake and fitness-to-drive assessment, accurate and early identification of sleepiness is essential. However, in the absence of a standardised definition and a time-efficient scoring method of MSEs, these short fragments are not assessed in clinical routine. Based on data of moderately sleepy patients, we recently developed the Bern continuous and high-resolution wake-sleep (BERN) criteria for visual scoring of MSEs and corresponding machine learning algorithms for automatic MSE detection, both mainly based on the electroencephalogram (EEG). The present study aimed to investigate the relationship between automatically detected MSEs and driving performance in a driving simulator, recorded in parallel with EEG, and to assess algorithm performance for MSE detection in severely sleepy participants. Methods: Maintenance of wakefulness test (MWT) and driving simulator recordings of 18 healthy participants, before and after a full night of sleep deprivation, were retrospectively analysed. Performance of automatic detection was compared with visual MSE scoring, following the BERN criteria, in MWT recordings of 10 participants. Driving performance was measured by the standard deviation of lateral position and the occurrence of off-road events. Results: In comparison to visual scoring, automatic detection of MSEs in participants with severe sleepiness showed good performance (Cohen's kappa = 0.66). The MSE rate in the MWT correlated with the latency to the first MSE in the driving simulator (r s = -0.54, p < 0.05) and with the cumulative MSE duration in the driving simulator (r s = 0.62, p < 0.01). No correlations between MSE measures in the MWT and driving performance measures were found. In the driving simulator, multiple correlations between MSEs and driving performance variables were observed. Conclusion: Automatic MSE detection worked well, independent of the degree of sleepiness. The rate and the cumulative duration of MSEs could be promising sleepiness measures in both the MWT and the driving simulator. The correlations between MSEs in the driving simulator and driving performance might reflect a close and time-critical relationship between sleepiness and performance, potentially valuable for the fitness-to-drive assessment.
| S-EPMC6990913 | biostudies-literature