Physical fitness and motor ability parameters as predictors for skateboarding performance: A logistic regression modelling analysis
The identification and prediction of athletic talent are pivotal in the development of successful sporting careers. Traditional subjective assessment methods have proven unreliable due to their inherent subjectivity, prompting the rise of data-driven techniques favoured for their objectivity. This e...
| Main Authors: | Aina Munirah, Ab Rasid, Rabiu Muazu, Musa, Abdul Majeed, Anwar P. P., Maliki, Ahmad Bisyri Husin Musawi, Mohamad Razali, Abdullah, Mohd Azraai, Mohd Razman, Noor Azuan, Abu Osman |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science
2024
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/41132/ http://umpir.ump.edu.my/id/eprint/41132/1/Physical%20fitness%20and%20motor%20ability%20parameters%20as%20predictors%20for%20skateboarding%20performance.pdf |
Similar Items
A cluster analysis and artificial neural network of identifying skateboarding talents based on bio-fitness indicators
by: Aina Munirah, Ab Rasid, et al.
Published: (2023)
by: Aina Munirah, Ab Rasid, et al.
Published: (2023)
The classification of skateboarding tricks via transfer learning pipelines
by: Muhammad Amirul, Abdullah, et al.
Published: (2021)
by: Muhammad Amirul, Abdullah, et al.
Published: (2021)
The classification of skateboarding Trick Manoeuvres: A Frequency-Domain Evaluation
by: Ibrahim, Muhammad Ar Rahim, et al.
Published: (2020)
by: Ibrahim, Muhammad Ar Rahim, et al.
Published: (2020)
The classification of skateboarding tricks : A transfer learning and machine learning approach
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2020)
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2020)
The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach
by: Muhammad Ar Rahim, Ibrahim, et al.
by: Muhammad Ar Rahim, Ibrahim, et al.
The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning and Machine Learning Models
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2020)
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2020)
The classification of skateboarding tricks: A support vector machine hyperparameter evaluation optimisation
by: Muhammad Ar Rahim, Ibrahim, et al.
Published: (2021)
by: Muhammad Ar Rahim, Ibrahim, et al.
Published: (2021)
The classification of skateboarding tricks by means of the integration of transfer learning models and K-Nearest neighbors
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2022)
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2022)
The classification of skateboarding trick manoeuvres through the integration of IMU and machine learning
by: Muhammad Amirul, Abdullah, et al.
Published: (2020)
by: Muhammad Amirul, Abdullah, et al.
Published: (2020)
An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning
by: Muhammad Amirul, Abdullah, et al.
Published: (2023)
by: Muhammad Amirul, Abdullah, et al.
Published: (2023)
A cluster analysis of identifying team and individual sports athlete based on anthropometric, health and skill related components
by: Noor Aishah, Kamarudin, et al.
Published: (2022)
by: Noor Aishah, Kamarudin, et al.
Published: (2022)
Kinematic variables defining performance of basketball free-throw in novice children : An information gain and logistic regression analysis
by: Afrouzeh, Mohsen, et al.
Published: (2022)
by: Afrouzeh, Mohsen, et al.
Published: (2022)
Kinematic variables defining performance of basketball free-throw in novice children : An information gain and logistic regression analysis
by: Afrouzeh, Mohsen, et al.
Published: (2022)
by: Afrouzeh, Mohsen, et al.
Published: (2022)
The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier
by: Mohamad Radzi, Mohd Sojak, et al.
Published: (2018)
by: Mohamad Radzi, Mohd Sojak, et al.
Published: (2018)
The classification of skateboarding trick manoeuvres through the integration of image processing techniques and machine learning
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2019)
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2019)
The Effect of Image Input Transformation from Inertial Measurement Unit Data on the Classification of Skateboarding Tricks
by: Muhammad Amirul, Abdullah, et al.
Published: (2021)
by: Muhammad Amirul, Abdullah, et al.
Published: (2021)
The classification of skateboarding tricks by means of support vector machine: An evaluation of significant time-domain features
by: Muhammad Amirul, Abdullah, et al.
Published: (2020)
by: Muhammad Amirul, Abdullah, et al.
Published: (2020)
The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
by: Zahari, Taha, et al.
Published: (2018)
by: Zahari, Taha, et al.
Published: (2018)
Talent identification of potential archers through fitness and motor ability performance variables by means of artificial neural network
by: Zahari, Taha, et al.
Published: (2018)
by: Zahari, Taha, et al.
Published: (2018)
Logistic regression modelling of mathematics ability among university undergraduate students.
by: Ahmad Tarmizi, Rohani, et al.
by: Ahmad Tarmizi, Rohani, et al.
New Test Statistics To Assess The
Goodness-Of-Fit Of
Logistic Regression Models
by: Hussain, Jassim Nassir
Published: (2013)
by: Hussain, Jassim Nassir
Published: (2013)
Embodiment in skateboarding videogames
by: Martin, Paul
Published: (2013)
by: Martin, Paul
Published: (2013)
Skateboarders vs Minimalism
by: Gladwell, Shaun
Published: (2016)
by: Gladwell, Shaun
Published: (2016)
Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression
by: Green, Martin J., et al.
Published: (2009)
by: Green, Martin J., et al.
Published: (2009)
A regression-based goodness-of-fit test statistic for the standard logistic distribution
by: Lim, Fong Peng, et al.
Published: (2009)
by: Lim, Fong Peng, et al.
Published: (2009)
Diagnostics of fitted binary logistic regression model based on individual subjects and covariate patterns
by: Sarkar, S. K., et al.
Published: (2010)
by: Sarkar, S. K., et al.
Published: (2010)
Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
by: Zahari, Taha, et al.
Published: (2017)
by: Zahari, Taha, et al.
Published: (2017)
A machine learning approach of predicting high potential archers by means of physical fitness indicators
by: Musa, Rabiu Muazu, et al.
Published: (2019)
by: Musa, Rabiu Muazu, et al.
Published: (2019)
Psycho-fitness parameters in the identification of high-potential archers
by: Rabiu Muazu, Musa, et al.
Published: (2019)
by: Rabiu Muazu, Musa, et al.
Published: (2019)
Development of Anthro-Fitness Model for evaluating firefighter recruits’ performance readiness using machine learning
by: Borhanudin, Mohd Yusof @ Mohamed, et al.
Published: (2024)
by: Borhanudin, Mohd Yusof @ Mohamed, et al.
Published: (2024)
Development of anthro-fitness model for evaluating firefighter recruits' performance readiness using machine learning
by: Borhanudin, Mohd Yusof @ Mohamed, et al.
Published: (2024)
by: Borhanudin, Mohd Yusof @ Mohamed, et al.
Published: (2024)
On comparison between logistic regression and geographically weighted logistic regression: with application to Indonesian poverty data
by: Saefuddin, Asep, et al.
Published: (2012)
by: Saefuddin, Asep, et al.
Published: (2012)
Developing a durable green electric skateboard
by: Tng, Wam Chen
Published: (2017)
by: Tng, Wam Chen
Published: (2017)
Robust Diagnostics In Logistic Regression Model
by: Ariffin @ Mat Zin, Syaiba Balqish
Published: (2010)
by: Ariffin @ Mat Zin, Syaiba Balqish
Published: (2010)
The likelihood of choosing alternative source of collagen among consumers: logistic regression approach
by: Duasa, Jarita, et al.
Published: (2020)
by: Duasa, Jarita, et al.
Published: (2020)
Robust logistic diagnostic for the identification of high leverage points in logistic regression model
by: Ariffin @ Mat Zin, Syaiba Balqish, et al.
Published: (2010)
by: Ariffin @ Mat Zin, Syaiba Balqish, et al.
Published: (2010)
The effects of musical fit on consumers' ability to freely recall related products.
by: Yeaoh, Joanne P. S., et al.
Published: (2010)
by: Yeaoh, Joanne P. S., et al.
Published: (2010)
Logistic regression for spatial Gibbs point processes
by: Baddeley, Adrian, et al.
Published: (2014)
by: Baddeley, Adrian, et al.
Published: (2014)
Logistic Regression Methods with Truncated Newton Method
by: Jasni, Mohamad Zain, et al.
Published: (2012)
by: Jasni, Mohamad Zain, et al.
Published: (2012)
Loan eligibility classification using logistic regression
by: Lik Pao, Paul Law, et al.
Published: (2023)
by: Lik Pao, Paul Law, et al.
Published: (2023)
Similar Items
-
A cluster analysis and artificial neural network of identifying skateboarding talents based on bio-fitness indicators
by: Aina Munirah, Ab Rasid, et al.
Published: (2023) -
The classification of skateboarding tricks via transfer learning pipelines
by: Muhammad Amirul, Abdullah, et al.
Published: (2021) -
The classification of skateboarding Trick Manoeuvres: A Frequency-Domain Evaluation
by: Ibrahim, Muhammad Ar Rahim, et al.
Published: (2020) -
The classification of skateboarding tricks : A transfer learning and machine learning approach
by: Muhammad Nur Aiman, Shapiee, et al.
Published: (2020) -
The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach
by: Muhammad Ar Rahim, Ibrahim, et al.