Search Results - Musa, S.

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  1. 1

    Machine learning analysis of intensity profiles and key indicators in standard microcycle of professional male soccer players

    Pillitteri, G., Musa, R. M., Clemente, F. M., Bongiovanni, T., Petrucci, M., Bianco, A., Beato, M., Battaglia, G.
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  2. 2

    Maschinelles Lernen im Hochleistungsskateboarding (Machine learning in high-performance skateboarding)

    Musa, R. M., Rasid, A. M. A., Samsudin, C. N. C., Majeed, A. P. P. A., Abdullah, M. R.
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  3. 3

    VAR consultation patterns and their association with fouls and misconduct: an analysis of the top five European football leagues

    Nazarudin, M. N., Abdul Majeed, A. P. P., Musa, R. M., Raj, N. B., Kuan, G., Abu Osman, N. A.
    Published in PLOS ONE (2025)
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  4. 4

    Associations between internal and external load parameters and match outcomes in men`s volleyball: a machine learning approach

    Lima, R. F., Musa, R. M., de Oliveira Castro, H., Clemente, F. M.
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  5. 5

    Test-retest reliability of customised inertial measurement units (IMUs) in evaluating skateboarding related manoeuvres

    Ab Rasid, A. M., Musa, A., Abdullah, M. A., Abdul Majeed, A. P. P., Mohd Razmaan, M. A., Abdullah, M. R., Abu Osman, N. A., Musa, R. M.
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  6. 6

    Personalized workload management in badminton using a machine learning model

    Musa, R. M., Abdul Majeed, A. P. P., Musawi Maliki, A. B. H., Kosni, N. A.
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  7. 7

    Comparing locomotor intensity indicators in soccer training and competition across contextual factors: a study of replaced coaches in a Portuguese professional 1st league team

    Sousa, H., Clemente, F. M., Sarmento, H., Gouveia, É. R., Musa, R. M.
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  8. 8

    Physical fitness and motor ability parameters as predictors for skateboarding performance: A logistic regression modelling analysis

    Ab Rasid, A. M., Muazu Musa, R., Abdul Majeed, A. P., Musawi Maliki, A. B. H., Abdullah, M. R., Mohd Razmaan, M. A., Abu Osman, N. A.
    Published in PLOS ONE (2024)
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  9. 9

    Identification of high-performance volleyball players from anthropometric variables and psychological readiness: A machine-learning approach

    Musa, R. M., Abdul Majeed, A. P. P., Suhaimi, M. Z., Abdullah, M. R., Razman, M. A. M., Abdelhakim, D., Osman, N. A. A.
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  10. 10

    Coaches` opinions about teaching defensive skills for youth handball teams

    da Silva Musa, V., Menezes, R. P.
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  11. 11

    Covid-19 lockdown: a global study investigating the effect of athletes' sport classification and sex on training practices

    Washif, J. A., Sandbakk, Ø., Seiler, S., Haugen, T., Farooq, A., Quarrie, K., van Rensburg, D. C. J., Krug, I., Verhagen, E., Wong, D. P., Mujika, I., Cortis, C., Haddad, M., Ahmadian, O., Al Jufaili, M., Al-Horani, R. A., Al-Mohannadi, A. S., Aloui, A., Ammar, A., Arifi, F., Aziz, A. R., Batuev, M., Beaven, C. M., Beneke, R., Bici, A., Bishnoi, P., Bogwasi, L., Bok, D., Boukhris, O., Boullosa, D., Bragazzi, N., Brito, J., Cartagena, R. P. P., Chaouachi, A., Cheung, S. S., Chtourou, H., Cosma, G., Debevec, T., DeLang, M. D., Dellal, A., Dönmez, G., Driss, T., Duque, J. D. P., Eirale, C., Elloumi, M., Foster, C., Franchini, E., Fusco, A., Galy, O., Gastin, P. B., Gill, N., Girard, O., Gregov, C., Halson, S., Hammouda, O., Hanzlíková, I., Hassanmirzaei, B., Hébert-Losier, K., Helú, H. M., Herrera-Valenzuela, T., Hettinga, F. J., Holtzhausen, L., Hue, O., Iacono, A. D., Ihalainen, J. K., James, C., Joseph, S., Kamoun, K., Khaled, M., Khalladi, K., Kim, K. J., Kok, L. Y., MacMillan, L., Mataruna-Dos-Santos, L. J., Matsunaga, R., Memishi, S., Millet, G. P., Moussa-Chamari, I., Musa, D. I., Nguyen, H. M. T., Nikolaidis, P. T., Owen, A., Padulo, J., Pagaduan, J. C., Perera, N. P., Pérez-Gómez, J., Pillay, L., Popa, A., Pudasaini, A., Rabbani, A., Rahayu, T., Romdhani, M., Salamh, P., Sarkar, A. S., Schillinger, A., Setyawati, H., Shrestha, N., Suraya, F., Tabben, M., Trabelsi, K., Urhausen, A., Valtonen, M., Weber, J., Whiteley, R., Zrane, A., Zerguini, Y., Zmijewski, P., Saad, H. B., Pyne, D. B., Taylor, L., Chamari, K.
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    “…Musa, D. I.…”
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  12. 12

    Olympic Games in COVID-19 times: lessons learned with special focus on the upcoming FIFA World Cup Qatar 2022

    Dergaa, I., Ben Saad, H., Souissi, A., Musa, S., Abdulmalik, M. A., Chamari, K.
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  13. 13

    FIFA World Cup 2022: What can we learn from the inspiring Tokyo 2020 Olympic Games held in COVID-19 times?

    Dergaa, I., Musa, S., Romdhani, M., Souissi, A., Abdulmalik, M., Chamari, K., Saad, H. B.
    Published in Biology of Sport (2022)
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  14. 14

    Training during the COVID-19 lockdown: Knowledge, beliefs, and practices of 12,526 athletes from 142 countries and six continents

    Washif, J. A., Farooq, A., Krug, I., Pyne, D. P., Verhagen, E., Taylor, L., Wong, D. P., Mujika, I., Cortis, C., Haddad, M., Ahmadian, O., Al Jufaili, M., Al-Horani, R. A., Al-Mohannadi, A. S., Aloui, A., Ammar, A., Arifi, F., Aziz, A. R., Batuev, M., Beaven, C. M., Beneke, R., Bici, A., Bishnoi, P., Bogwasi, L., Bok, D., Boukhris, O., Boullosa, D., Bragazzi, N., Brito, J., Palacios Cartagena, R. P., Chaouachi, A., Cheung, S. S., Chtourou, H., Cosma, G., Debevec, T., DeLang, M. D., Dellal, A., Dönmez, G., Driss, T., Peña Duque, J. D., Eirale, C., Elloumi, M., Foster, C., Franchini, E., Fusco, A., Galy, O., Gastin, P. G., Gill, N., Girard, O., Gregov, C., Halson, S., Hammouda, O., Hanzlíková, I., Hassanmirzaei, B., Haugen, T., Hébert-Losier, K., Muñoz Helú, H., Herrera-Valenzuela, T., Hettinga, F. J., Holtzhausen, L., Hue, O., Dello Iacono, A., Ihalainen, J. K., James, C., Janse van Rensburg, D. C., Joseph, S., Kamoun, K., Khaled, M., Khalladi, K., Kim, K. J., Kok, L.-Y., MacMillan, L., Mataruna-Dos-Santos, L. J., Matsunaga, R., Memishi, S., Millet, G. P., Moussa-Chamari, I., Musa, D. I., Thuan Nguyen, H. M., Nikolaidis, P. T., Owen, A., Padulo, J., Cayaban Pagaduan, J., Panagodage Perera, N., Pérez-Gómez, J., Pillay, L., Popa, A., Pudasaini, A., Rabbani, A., Rahayu, T., Romdhani, M., Salamh, P., Sarkar, A.-S., Schillinger, A., Seiler, S., Setyawati, H., Shrestha, N., Suraya, F., Tabben, M., Trabelsi, K., Urhausen, A., Valtonen, M., Weber, J., Whiteley, R., Zrane, A., Zerguini, Y., Zmijewski, P., Sandbakk, Ø., Ben Saad, H., Camari, K.
    Published in Sports Medicine (2021)
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    “…Musa, D. I.…”
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  15. 15

    The classification of skateboarding tricks via transfer learning pipelines

    Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Zakaria, M. A., Razman, M. A. M., Musa, R. M., Osman, N. A. A., Majeed, A. P. A.
    Published in PeerJ Computer Science (2021)
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  16. 16

    COVID-19 vaccination, herd immunity and the transition toward normalcy: Challenges with the upcoming sports event

    Dergaa, I., Abdelrahman, H., Varma, A., Yousfi, N., Souissi, A., Ghram, A., Hammad, A. S., Musa, E. R., Taheri, M., Irandoust, K., Chtourou, H., Rafiei, M. M., Ghasemi, M., Farzian, S.
    Published in Annals of Applied Sport Science (2021)
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    “…Musa, E. R.…”
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  17. 17

    COVID-19 and Brazilian handball coaches: impacts on training prescription and professional learning

    da Silva Musa, V., Romário dos Santos, W., Pombo Menezes, R., Costa, V., Aquino, R., Pombo Menezes, R.
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  18. 18

    The classification of skateboarding tricks by means of support vector machine: An evaluation of significant time-domain features

    Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Majeed, A. P. A., Razman, M. A. M., Musa, R. M., Zakaria, M. A.
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  19. 19

    The classification of skateboarding trick manoeuvres through the integration of IMU and machine learning

    Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Razman, M. A. M., Musa, R. M., Majeed, A. P. A.
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  20. 20

    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach

    Ibrahim, M. A. R., Abdullah, M. A., Shapiee, M. N. A., Razman, M. A. M., Musa, R. M., Zakaria, M. A., Osman, N. A. A., Majeed, A. P. A.
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