Using Machine Learning Algorithms for Jumping Distance Prediction of Male Long Jumpers

dc.contributor.authorİncetaş, Mürsel Ozan
dc.contributor.authorUçar, Murat
dc.contributor.authorBayraktar, Işık
dc.contributor.authorÇilli, Murat
dc.date.accessioned2023-07-31T13:08:45Z
dc.date.available2023-07-31T13:08:45Z
dc.date.issued2022
dc.departmentALKÜ, Fakülteler, Spor Bilimleri Fakültesi, Antrenörlük Eğitimi Bölümü
dc.description.abstractThe long jump is defined as an athletic event, and it has also been a standard event in modern Olympic Games. The purpose of the athletes is to make the distance as far as possible from a jumping point. The main purpose of this study was to determine the most successful machine learning algorithm in the prediction of the long jump distance of male athletes. In this paper, we used age and velocity variables for predicting the long jump performance of athletes. During the research, 328 valid jumps belonging to 73 Turkish male athletes were used as data. In determining the most successful algorithm, mean absolute error (MAE), root mean square error (RMSE), Mean Squared Error (MSE), R2 score, Explained Variance Score (EVS), and Mean Squared Logarithmic Error (MSLE) values were taken into consideration. The outcomes of the analysis showed that long jump performance can be determined by chosen independent variables. The 5-fold cross-validation technique was used for the performance evaluation of the models. As a result of the experimental tests, the Gradient Boosting Regression Trees (GBRT) algorithm reached the best result with an MSE value of 0.0865. In this study, it was concluded that the machine learning approach suggested can be used by trainers to determine the long jump performance of male athletes.
dc.identifier.doi10.38016/jista.1078474
dc.identifier.endpage152en_US
dc.identifier.issue2en_US
dc.identifier.startpage145en_US
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1122767/using-machine-learning-algorithms-for-jumping-distance-prediction-of-male-long-jumpers
dc.identifier.urihttps://hdl.handle.net/20.500.12868/2323
dc.identifier.volume5en_US
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofZeki Sistemler Teori ve Uygulamaları Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectLong
dc.subjectLong Jump Performance
dc.subjectMachine Learning
dc.subjectRun-up Velocity
dc.titleUsing Machine Learning Algorithms for Jumping Distance Prediction of Male Long Jumpers
dc.typeArticle

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