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A New Reliable Performance Analysis Template for Quantifying Action Variables in Elite Men's Wheelchair Basketball.

ABSTRACT: This study aimed to develop a valid and reliable performance analysis template for quantifying team action variables in elite men's wheelchair basketball. First action variables and operational definitions were identified by the authors and verified by an expert panel of wheelchair basketball coaching staff in order to establish expert validity. A total of 109 action variable were then placed into 17 agreed Categorical Predictor Variable categories. The action variables were then used to develop a computerized performance analysis template for post-event analysis. Each possession (n = 200) from an international men's wheelchair basketball game was analyzed by the first author on two occasions for assessment of intra-observer reliability and by a coach and a performance analyst for inter-observer reliability. Percentage error and Weighted Kappa coefficients were calculated to compare the levels of error and agreement for each action variable. Intra-observer reliability demonstrated perfect or almost perfect agreement (

SUBMITTER: Francis J

PROVIDER: S-EPMC6352711 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A New Reliable Performance Analysis Template for Quantifying Action Variables in Elite Men's Wheelchair Basketball.

Francis John J Owen Alun A Peters Derek M DM

Frontiers in psychology 20190123

This study aimed to develop a valid and reliable performance analysis template for quantifying team action variables in elite men's wheelchair basketball. First action variables and operational definitions were identified by the authors and verified by an expert panel of wheelchair basketball coaching staff in order to establish expert validity. A total of 109 action variable were then placed into 17 agreed Categorical Predictor Variable categories. The action variables were then used to develop ...[more]

PMID: 30728791

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Project description:The purposes of this study were to (i) develop a field-goal shooting performance analysis template and (ii) explore the impact of each identified variable upon the likely outcome of a field-goal attempt using binary logistic regression modelling in elite men's wheelchair basketball. First, a field-goal shooting performance analysis template was developed that included 71 Action Variables (AV) grouped within 22 Categorical Predictor Variables (CPV) representing offensive, defensive and game context variables. Second, footage of all 5,105 field-goal attempts from 12 teams during the men's 2016 Rio De Janeiro Paralympic Games wheelchair basketball competition were analysed using the template. Pearson's chi-square analyses found that 18 of the CPV were significantly associated with field-goal attempt outcome (p < 0.05), with seven of them reaching moderate association (Cramer's V: 0.1-0.3). Third, using 70% of the dataset (3,574 field-goal attempts), binary logistic regression analyses identified that five offensive variables (classification category of the player, the action leading up to the field-goal attempt, the time left on the clock, the location of the shot, and the movement of the player), two defensive variables (the pressure being exerted by the defence, and the number of defenders within a 1-meter radius) and 1 context variable (the finishing position of the team in the competition) affected the probability of a successful field-goal attempt. The quality of the developed model was determined acceptable (greater than 65%), producing an area under the curve value of 68.5% when the model was run against the remaining 30% of the dataset (1,531 field-goal attempts). The development of the model from such a large sample of objective data is unique. As such it offers robust empirical evidence to enable coaches, performance analysts and players to move beyond anecdote, in order to appreciate the potential effect of various and varying offensive, defensive and contextual variables on field-goal success.

Project description:Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men's wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modeling. The valid and reliable template developed Francis et al. (2019) was used to analyze video footage in SportsCode from 31 games at the men's 2015 European Wheelchair Basketball Championships. The 31 games resulted in 6,126 rows of data which were exported and converted into a CSV file, analyzed using R (R Core Team, 2015) and subjected to a data modeling process. Chi-square analyses identified significant (p < 0.05) relationships between Game Outcome and 19 Categorical Predictor Variables. Automated stepwise binary regression model building was completed using 70% of the data (4,282 possessions) and produced a model that included 12 Categorical Predictor Variables. The accuracy of the developed model was deemed to be acceptable at accurately predicting the remaining 30% of the data (1,844 possessions) and produced an area under the receiver operating characteristic curve value of 0.759. The model identified the odds of winning are more than double when the team in possession are in a state of winning at the start of the possession are increased five-fold when the offensive team do not use a 1.0 or 1.5 classified player, but are increased six-fold when the offensive team use three or more 3.0 or 3.5 players. The final model can be used by coaches, players and support staff to devise training and game strategies that involve selecting the most appropriate offensive and defensive approaches when performing ball possessions to enhance the likelihood of winning in elite men's wheelchair basketball.

Project description:In this paper, we present the ON score for evaluating the performance of athletes and teams that includes a season-long evaluation system, a single-game evaluation, and an evaluation of an athlete's overall contribution to their team. The approach used to calculate the ON score is based on mixed-effects regression models that take into account the hierarchical structure of the data and a principal component analysis to calculate athlete rating. We apply our methodology to a large dataset of National Basketball Association (NBA) games spanning four seasons from 2015-2016 to 2018-2019. Our model is validated using two systematic approaches, and our results demonstrate the reliability of our approach to calculate an athlete's performance. This provides coaches, General Managers and player agents with a powerful tool to gain deeper insights into their players' performance, make more informed decisions and ultimately improve team performance. Our methodology has several key advantages. First, by incorporating the hierarchical structure of the data, we can obtain valuable information about an athlete's contribution within their team. Second, the use of principal component analysis allows us to calculate a single score, the ON score, that captures the overall performance of an athlete. Third, our approach is based on classical restricted likelihood methods, which makes the calculation faster than Bayesian methods typically requiring 1000 posterior samples. With our approach, coaches and managers can evaluate athletes' performance throughout the season, compare athletes and teams over a year, and assess an athlete's performance during a single game. Our methodology can also complement other ratings and box score metrics to provide a more comprehensive assessment of an athlete's performance as our method uses the hierarchical nature of performance data (i.e. player nested within team over season) which is typically ignored in player rating systems. In summary, our methodology represents a significant contribution to the field of sports analytics and provides the foundation for future developments.

Project description:Wheelchair basketball has evolved into a high-performance sport over several years, and small variations in player performance can determine the difference between winning and losing. Therefore, adequate micronutrient intake may influence this difference if performance-promoting macronutrient intake and physical fitness are equal between teams. Seventeen elite male wheelchair basketball players belonging to the Spanish National Team participated in this study. Macro- and micronutrient intake were determined using a food-weighing diary over three consecutive days during three training camps in two consecutive years. Current Dietary Reference Intake levels were used to determine the adequacy of intake of seventeen micronutrients of particular interest for athletes. After categorizing the consumed foods into fourteen food groups according to the National Nutrient Database for Standard References (USDA) these groups were used to identify the best predictors of the adequacy of intake for each micronutrient. Total energy intake correlated positively with the adequacy of all micronutrient intake levels, except for vitamins A and E. Five B vitamins and phosphorus, selenium, and iron showed 100% adequacy. All other micronutrient intake levels were found to be inadequate, e.g., vitamin E (51% adequacy) and calcium (73%). The fruit, fish and cereal food groups were found to be predictors of adequate intake of most micronutrients. Together with energy intake (p = .009, ?2 = 0.49), the intake of the fruit (p = .032, ?2 = 0.39) and egg (p = .036, Kendall's W = 0.42) food groups increased significantly over time, along with improved iodine (p = .008, W = 0.61) and magnesium (p = .030, W = 0.44) adequacy levels. Because the adequacy of micronutrient intake correlates positively with energy intake (R = 0.64, p < .001), a varied diet that includes cereals, fish and fruits is especially important for players with low levels of energy intake. Supplements may be a possible solution if adequate micronutrient intake cannot be achieved through regular dietary intake alone. However, dietary analyses should be conducted on a regular basis throughout the year to improve the nutritional knowledge of the athletes and assure adequate micronutrient intake.

Dataset Information

A New Reliable Performance Analysis Template for Quantifying Action Variables in Elite Men's Wheelchair Basketball.

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A New Reliable Performance Analysis Template for Quantifying Action Variables in Elite Men's Wheelchair Basketball.

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