Umile Giuseppe Longo1,2, Francesco Sofi3,4, Vincenzo Candela5, Laura Risi Ambrogioni6, Giuditta Pagliai7, Carlo Massaroni8, Emiliano Schena9, Matteo Cimmino10, Fabrizio D'Ancona11, Vincenzo Denaro12,13. 1. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. g.longo@unicampus.it. 2. Centro Integrato di Ricerca (CIR), Campus Bio-Medico University, Rome, Italy. g.longo@unicampus.it. 3. Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy. francesco.sofi@unifi.it. 4. Don Carlo Gnocchi Foundation, Onlus IRCCS, Florence, Italy. francesco.sofi@unifi.it. 5. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. v.candela@unicampus.it. 6. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. laura.ambrogioni@gmail.com. 7. Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy. giuditta.pagliai@gmail.com. 8. Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Campus Bio-Medico University, Rome, Italy. c.massaroni@unicampus.it. 9. Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Campus Bio-Medico University, Rome, Italy. e.schena@unicampus.it. 10. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. cimmino.cbm@gmail.com. 11. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. dancona.cbm@gmail.com. 12. Department of Orthopaedic and Trauma Surgery, Campus Bio-Medico University, Via Alvaro del Portillo, 200, Trigoria,, 00128, Rome, Italy. denaro.cbm@gmail.com. 13. Centro Integrato di Ricerca (CIR), Campus Bio-Medico University, Rome, Italy. denaro.cbm@gmail.com.
Abstract
BACKGROUND: Our previous study on the 2016/2017 Serie A season showed that a greater likelihood of reaching the top positions in the Italian league "Serie A" seemed to be mainly related to sprint activity, goal attempts, total throws, target shots and assists. Therefore, we aim to evaluate the following season data in the same league to compare, confirm, and improve these results. METHODS: The data of all the matches played during the "Serie A" 2017-2018 season were obtained from the Italian soccer league. The teams' analysis was performed in terms of total distance covered in km, jogging, running and sprint activities, average speed, and match statistics (total shots, shots on target, goal attempts, assists, turnovers, and steals). RESULTS: Teams that reached the first four positions revealed a lower percentage of running (65.98 ± 1.51 vs. 66.84 ± 2.18; p < 0.001), a higher percentage of jogging (25.61 ± 1.71 vs. 25.30 ± 1.97; p = 0.037) and sprint activities (8.41 ± 1.04 vs. 7.86 ± 0.82; p < 0.001). Match statistics seem to be statistically different between the first four teams the other teams. The total goals are strongly associated both with the total score at the end of the championship (R = 0.906; p < 0.001) and with the position in the final ranking (R = 0.850; p < 0.001). CONCLUSIONS: Our results suggest that high-level teams have a lower running rate and a higher percentage of jogging and sprinting than other teams.
BACKGROUND: Our previous study on the 2016/2017 Serie A season showed that a greater likelihood of reaching the top positions in the Italian league "Serie A" seemed to be mainly related to sprint activity, goal attempts, total throws, target shots and assists. Therefore, we aim to evaluate the following season data in the same league to compare, confirm, and improve these results. METHODS: The data of all the matches played during the "Serie A" 2017-2018 season were obtained from the Italian soccer league. The teams' analysis was performed in terms of total distance covered in km, jogging, running and sprint activities, average speed, and match statistics (total shots, shots on target, goal attempts, assists, turnovers, and steals). RESULTS: Teams that reached the first four positions revealed a lower percentage of running (65.98 ± 1.51 vs. 66.84 ± 2.18; p < 0.001), a higher percentage of jogging (25.61 ± 1.71 vs. 25.30 ± 1.97; p = 0.037) and sprint activities (8.41 ± 1.04 vs. 7.86 ± 0.82; p < 0.001). Match statistics seem to be statistically different between the first four teams the other teams. The total goals are strongly associated both with the total score at the end of the championship (R = 0.906; p < 0.001) and with the position in the final ranking (R = 0.850; p < 0.001). CONCLUSIONS: Our results suggest that high-level teams have a lower running rate and a higher percentage of jogging and sprinting than other teams.
Entities:
Keywords:
Elite football; Football; Match statistics; Performance analysis; Serie A; Soccer; Sport
Authors: Ricardo M L Barros; Milton S Misuta; Rafael P Menezes; Pascual J Figueroa; Felipe A Moura; Sergio A Cunha; Ricardo Anido; Neucimar J Leite Journal: J Sports Sci Med Date: 2007-06-01 Impact factor: 2.988
Authors: Toni Modric; James J Malone; Sime Versic; Marcin Andrzejewski; Paweł Chmura; Marek Konefał; Patrik Drid; Damir Sekulic Journal: BMC Sports Sci Med Rehabil Date: 2022-10-10