Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis

References

• Abbott, W., Brownlee, T. E., Harper, L. D., Naughton, R. J., Richardson, A., & Clifford, T. (2019). A season long investigation into the effects of injury, match selection and training load on mental wellbeing in professional under 23 soccer players: A team case study. European Journal of Sport Science, 19(9), 1250–1256. https://doi.org/10.1080/17461391.2019.1600586
   PubMed Web of Science ®Google Scholar
• Abdullah, M., Maliki, A., Musa, R., Kosni, N., & Juahir, H. (2016). Intelligent prediction of soccer technical skill on youth soccer player’s relative performance using multivariate analysis and artificial neural network techniques. International Journal on Advanced Science, Engineering and Information Technology, 6(5), 668–674. https://doi.org/10.18517/ijaseit.6.5.975
   Google Scholar
• Akenhead, R., Harley, J. A., & Tweddle, S. P. (2016). Examining the external training load of an English Premier League football team with special reference to acceleration. Journal of Strength & Conditioning Research, 30(9), 2424–2432. https://doi.org/10.1519/jsc.0000000000001343
   PubMed Web of Science ®Google Scholar
• Akubat, I., Barrett, S., & Abt, G. (2014). Integrating the internal and external training loads in soccer. International Journal of Sports Physiology & Performance, 9(3), 457–462. https://doi.org/10.1123/ijspp.2012-0347
   PubMed Web of Science ®Google Scholar
• Akubat, I., Barrett, S., Sagarra, M. L., & Abt, G. (2018). The validity of external: Internal training load ratios in rested and fatigued soccer players. Sports, 6(2), 44. https://doi.org/10.3390/sports6020044
   Google Scholar
• Alemdaroğlu, U. (2020). External and internal training load relationships in soccer players. Journal of Human Sport & Exercise, 16(2). https://doi.org/10.14198/jhse.2021.162.07
   Web of Science ®Google Scholar
• Arazi, H., Asadi, A., Khalkhali, F., Boullosa, D., Hackney, A. C., Granacher, U., & Zouhal, H. (2020). Association between the acute to chronic workload ratio and injury occurrence in young male team soccer players: A preliminary study. Frontiers in Physiology, 11, 608. https://doi.org/10.3389/fphys.2020.00608
   PubMed Web of Science ®Google Scholar
• Bacon, C. S., & Mauger, A. R. (2017). Prediction of overuse injuries in professional u18-u21 footballers using metrics of training distance and intensity. The Journal of Strength & Conditioning Research, 31(11), 3067–3076. https://doi.org/10.1519/JSC.0000000000001744
   PubMed Web of Science ®Google Scholar
• Bartlett, J. D., O’Connor, F., Pitchford, N., Torres-Ronda, L., & Robertson, S. J. (2017). Relationships between internal and external training load in team-Sport athletes: Evidence for an individualized approach. International Journal of Sports Physiology & Performance, 12(2), 230–234. https://doi.org/10.1123/ijspp.2015-0791
   PubMed Web of Science ®Google Scholar
• Beato, M., & Drust, B. (2021). Acceleration intensity is an important contributor to the external and internal training load demands of repeated sprint exercises in soccer players. Research in Sports Medicine, 29(1), 67–76. https://doi.org/10.1080/15438627.2020.1743993
   PubMed Web of Science ®Google Scholar
• Bowen, L., Gross, A. S., Gimpel, M., Bruce-Low, S., & Li, F. X. (2020). Spikes in acute: Chronic workload ratio (ACWR) associated with a 5–7 times greater injury rate in English Premier League football players: A comprehensive 3-year study. British Journal of Sports Medicine, 54(12), 731–738. https://doi.org/10.1136/bjsports-2018-099422
   PubMed Web of Science ®Google Scholar
• Bowen, L., Gross, A. S., Gimpel, M., & Li, F.-X. (2017). Accumulated workloads and the acute: Chronic workload ratio relate to injury risk in elite youth football players. British Journal of Sports Medicine, 51(5), 452–459. https://doi.org/10.1136/bjsports-2015-095820
   PubMed Web of Science ®Google Scholar
• Buchheit, M., & Laursen, P. B. (2013). High-intensity interval training, solutions to the programming puzzle. Part II: Anaerobic energy, neuromuscular load and practical applications. Sports Medicine, 43(10), 927–954. https://doi.org/10.1007/s40279-013-0066-5
   PubMed Web of Science ®Google Scholar
• Casamichana, D., & Castellano, J. (2015). The relationship between intensity indicators in small-sided soccer games. Journal of Human Kinetics, 46(1), 119–128. https://doi.org/10.1515/hukin-2015-0040
   PubMed Web of Science ®Google Scholar
• Casamichana, D., Castellano, J., Calleja-Gonzalez, J., San Román, J., & Castagna, C. (2013). Relationship between indicators of training load in soccer players. Journal of Strength & Conditioning Research, 27(2), 369–374. https://doi.org/10.1519/JSC.0b013e3182548af1
   PubMed Web of Science ®Google Scholar
• Castagna, C., D’Ottavio, S., Cappelli, S., & Araújo Póvoas, S. C. (2019). The effects of long sprint ability–oriented small-Sided games using different ratios of players to pitch area on internal and external load in soccer players. International Journal of Sports Physiology & Performance, 14(9), 1265–1272. https://doi.org/10.1123/ijspp.2018-0645
   PubMed Web of Science ®Google Scholar
• Castillo, D., Weston, M., McLaren, S. J., Cámara, J., & Yanci, J. (2017). Relationships between internal and external match-load indicators in soccer match officials. International Journal of Sports Physiology & Performance, 12(7), 922–927. https://doi.org/10.1123/ijspp.2016-0392
   PubMed Web of Science ®Google Scholar
• Claudino, J. G., Capanema, D. O., de Souza, T. V., Serrão, J. C., Machado Pereira, A. C., & Nassis, G. P. (2019). Current approaches to the use of Artificial intelligence for injury risk assessment and performance prediction in team Sports: A systematic review. Sports Medicine - Open, 5(1), 28. https://doi.org/10.1186/s40798-019-0202-3
   PubMedGoogle Scholar
• Clemente, F. M., Rabbani, A., Conte, D., Castillo, D., Afonso, J., Truman Clark, C. C., Nikolaidis, P. T., Rosemann, T., and Knechtle, B. (2019). Training/Match external load ratios in professional soccer players: A full-season study. International Journal of Environmental Research and Public Health, 16(17), 3057. https://doi.org/10.3390/ijerph16173057
   PubMed Web of Science ®Google Scholar
• Coppalle, S., Ravé, G., Moran, J., Salhi, I., Abderrahman, A. B., Zouita, S., Granacher, U., and Zouhal, H. (2021). Internal and external training load in under-19 versus professional soccer players during the in-season period. International Journal of Environmental Research and Public Health, 18(2), 558. https://doi.org/10.3390/ijerph18020558
   PubMed Web of Science ®Google Scholar
• Costa, E. C., Vieira, C. M., Moreira, A., Ugrinowitsch, C., Castagna, C., & Aoki, M. S. (2013). Monitoring external and internal loads of brazilian soccer referees during official matches. Journal of Sports Science & Medicine, 12(3), 559–564.
   PubMed Web of Science ®Google Scholar
• Coutts, A. J., Crowcroft, S., & Kempton, T. (2017). Developing athlete monitoring systems. Kellmann, M., Beckmann, J. Sport, Recovery, and Performance: Interdisciplinary Insights. London: Routledge.
   Google Scholar
• Delaney, J. A., Duthie, G. M., Thornton, H. R., & Pyne, D. B. (2018). Quantifying the relationship between internal and external work in team sports: Development of a novel training efficiency index. Science and Medicine in Football, 2(2), 149–156. https://doi.org/10.1080/24733938.2018.1432885
   Web of Science ®Google Scholar
• Delecroix, B., McCall, A., Dawson, B., Berthoin, S., & Dupont, G. (2018). Workload and non-contact injury incidence in elite football players competing in European leagues. European Journal of Sport Science, 18(9), 1280–1287. https://doi.org/10.1080/17461391.2018.1477994
   PubMed Web of Science ®Google Scholar
• Derbidge, C., Moody, J. A., & Byrne, P. J. (2020). Can the use of an external: Internal ratio during standardised small-Sided games be a detector of fatigue in professional adolescent soccer players?
   Google Scholar
• Downs, S. H., & Black, N. (1998). The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. Journal of Epidemiology & Community Health, 52(6), 377–384. https://doi.org/10.1136/jech.52.6.377
   PubMed Web of Science ®Google Scholar
• Enes, A., Oneda, G., Alves, D. L., Palumbo, D. P., Cruz, R., Moiano Junior, J. V. M., Novack, L. F., and Osiecki, R. (2021). Determinant factors of the match-based internal load in elite soccer players. Research Quarterly for Exercise & Sport, 92(1), 63–70. https://doi.org/10.1080/02701367.2019.1710445
   PubMed Web of Science ®Google Scholar
• Foster, C. (1998). Monitoring training in athletes with reference to overtraining syndrome. Medicine & Science in Sports and Exercise, 30(7), 1164–1168. https://doi.org/10.1097/00005768-199807000-00023
   PubMed Web of Science ®Google Scholar
• Foster, C., Boullosa, D., McGuigan, M., Fusco, A., Cortis, C., Arney, B. E., Orton, B., Dodge, C., Jaime, S., Radtke, K., van Erp, T., de Koning, J. J., Bok, D., Rodriguez-Marroyo, J. A., and Porcari, J. P. (2021). 25 years of session rating of perceived exertion: Historical perspective and Development. International Journal of Sports Physiology & Performance, 16(5), 612–621. https://doi.org/10.1123/ijspp.2020-0599
   PubMed Web of Science ®Google Scholar
• Foster, C., Rodriguez-Marroyo, J. A., & de Koning, J. J. (2017). Monitoring training loads: The past, the present, and the future. International Journal of Sports Physiology & Performance, 12(Suppl 2), S22–s28. https://doi.org/10.1123/ijspp.2016-0388
   PubMedGoogle Scholar
• Fuller, C. W. (2018). Modeling the impact of players’ workload on the injury-burden of English Premier League football clubs. Scandinavian Journal of Medicine & Science in Sports, 28(6), 1715–1721. https://doi.org/10.1111/sms.13078
   PubMed Web of Science ®Google Scholar
• Gabbett, T. J., Whyte, D. G., Hartwig, T. B., Wescombe, H., & Naughton, G. A. (2014). The relationship between workloads, physical performance, injury and illness in adolescent male football players. Sports Medicine, 44(7), 989–1003. https://doi.org/10.1007/s40279-014-0179-5
   PubMed Web of Science ®Google Scholar
• Gallo, T., Cormack, S., Gabbett, T., Williams, M., & Lorenzen, C. (2015). Characteristics impacting on session rating of perceived exertion training load in Australian footballers. Journal of Sports Sciences, 33(5), 467–475. https://doi.org/10.1080/02640414.2014.947311
   PubMed Web of Science ®Google Scholar
• Gaudino, P., Iaia, F. M., Strudwick, A. J., Hawkins, R. D., Alberti, G., Atkinson, G., & Gregson, W. (2015). Factors influencing perception of effort (session rating of perceived exertion) during elite soccer training. International Journal of Sports Physiology & Performance, 10(7), 860–864. https://doi.org/10.1123/ijspp.2014-0518
   PubMed Web of Science ®Google Scholar
• Geurkink, Y., Vandewiele, G., Lievens, M., de Turck, F., Ongenae, F., Matthys, S. P. J., Boone, J., and Bourgois, J. G. (2019). Modeling the prediction of the session rating of perceived exertion in soccer: Unraveling the puzzle of predictive indicators. International Journal of Sports Physiology & Performance, 14(6), 841–846. https://doi.org/10.1123/ijspp.2018-0698
   PubMed Web of Science ®Google Scholar
• Giménez, J. V., Leicht, A. S., & Gomez, M. A. (2019). Physical performance differences between Starter and non-Starter players during professional soccer friendly matches. Journal of Human Kinetics, 69(1), 283–291. https://doi.org/10.2478/hukin-2019-0018
   PubMed Web of Science ®Google Scholar
• Gomez-Piriz, P. T., Jiménez-Reyes, P., & Ruiz-Ruiz, C. (2011). Relation between total body load and session rating of perceived exertion in professional soccer players. Journal of Strength & Conditioning Research, 25(8), 2100–2103. https://doi.org/10.1519/JSC.0b013e3181fb4587
   PubMed Web of Science ®Google Scholar
• González-Fimbres, R. A., Ramírez-Siqueiros, M. G., Reynoso-Sánchez, L. F., Quezada-Chacón, J. T., Miranda-Mendoza, J., & Hernández-Cruz, G. (2019). A new approach to quantify internal and external training load for intermittent sports. Biotecnia, 21(3), 26–34. https://doi.org/10.18633/biotecnia.v21i3.1008
   Web of Science ®Google Scholar
• Griffin, A., Kenny, I. C., Comyns, T. M., & Lyons, M. (2020). The association between the acute: Chronic workload ratio and injury and its application in team Sports: A systematic review. Sports Medicine, 50(3), 561–580. https://doi.org/10.1007/s40279-019-01218-2
   PubMed Web of Science ®Google Scholar
• Grünbichler, J., Federolf, P., & Gatterer, H. (2020). Workload efficiency as a new tool to describe external and internal competitive match load of a professional soccer team: A descriptive study on the relationship between pre-game training loads and relative match load. European Journal of Sport Science, 20(8), 1034–1041. https://doi.org/10.1080/17461391.2019.1697374
   PubMed Web of Science ®Google Scholar
• Hader, K., Rumpf, M. C., Hertzog, M., Kilduff, L. P., Girard, O., & Silva, J. R. (2019). Monitoring the athlete match response: Can external load variables predict post-match acute and residual fatigue in soccer? A systematic review with meta-analysis. Sports Medicine - Open, 5(1), 48. https://doi.org/10.1186/s40798-019-0219-7
   PubMedGoogle Scholar
• Howle, K., Waterson, A., & Duffield, R. (2020). Injury incidence and workloads during congested schedules in football. International Journal of Sports Medicine, 41(2), 75–81. https://doi.org/10.1055/a-1028-7600
   PubMed Web of Science ®Google Scholar
• Impellizzeri, F. M., Marcora, S. M., & Coutts, A. J. (2019). Internal and external training load: 15 years on. International Journal of Sports Physiology & Performance, 14(2), 270–273. https://doi.org/10.1123/ijspp.2018-0935
   PubMed Web of Science ®Google Scholar
• Impellizzeri, F. M., Menaspà, P., Coutts, A. J., Kalkhoven, J., & Menaspà, M. J. (2020). Training load and its role in injury prevention, part I: Back to the future. Journal of Athletic Training, 55(9), 885–892. https://doi.org/10.4085/1062-6050-500-19
   PubMed Web of Science ®Google Scholar
• Impellizzeri, F. M., Rampinini, E., & Marcora, S. M. (2005). Physiological assessment of aerobic training in soccer. Journal of Sports Sciences, 23(6), 583–592. https://doi.org/10.1080/02640410400021278
   PubMed Web of Science ®Google Scholar
• Jaspers, A., Brink, M. S., Probst, S. G., Frencken, W. G., & Helsen, W. F. (2017). Relationships between training load indicators and training outcomes in professional soccer. Sports Medicine, 47(3), 533–544. https://doi.org/10.1007/s40279-016-0591-0
   PubMed Web of Science ®Google Scholar
• Jaspers, A., De Beéck, T. O., Brink, M. S., Frencken, W. G. P., Staes, F., Davis, J. J., & Helsen, W. F. (2018). Relationships between the external and internal training load in professional soccer: What can we learn from Machine learning? International Journal of Sports Physiology & Performance, 13(5), 625–630. https://doi.org/10.1123/ijspp.2017-0299
   PubMed Web of Science ®Google Scholar
• Jaspers, A., Kuyvenhoven, J. P., Staes, F., Frencken, W. G. P., Helsen, W. F., & Brink, M. S. (2018). Examination of the external and internal load indicators’ association with overuse injuries in professional soccer players. Journal of Science & Medicine in Sport / Sports Medicine Australia, 21(6), 579–585. https://doi.org/10.1016/j.jsams.2017.10.005
   PubMed Web of Science ®Google Scholar
• Jeffries, A. C., Marcora, S. M., Coutts, A. J., Wallace, L., McCall, A., & Impellizzeri, F. M. (2021). Development of a revised conceptual framework of physical training for use in Research and practice. Sports Medicine, 52(4), 709–724. https://doi.org/10.1007/s40279-021-01551-5
   PubMed Web of Science ®Google Scholar
• Kaur, M., Ribeiro, D. C., Theis, J. C., Webster, K. E., & Sole, G. (2016). Movement patterns of the knee during gait following ACL reconstruction: A systematic review and meta-analysis. Sports Medicine, 46(12), 1869–1895. https://doi.org/10.1007/s40279-016-0510-4
   PubMed Web of Science ®Google Scholar
• Kotsiantis, S. B., Zaharakis, I., & Pintelas, P. (2007). Supervised machine learning: A review of classification techniques. Emerging Artificial Intelligence Applications in Computer Engineering, 160(1), 3–24.
   Google Scholar
• Lacome, M., Simpson, B., Broad, N., & Buchheit, M. (2018). Monitoring players’ readiness using predicted heart-rate responses to soccer drills. International Journal of Sports Physiology & Performance, 13(10), 1273–1280. https://doi.org/10.1123/ijspp.2018-0026
   PubMed Web of Science ®Google Scholar
• Lazarus, B. H., Stewart, A. M., White, K. M., Rowell, A. E., Esmaeili, A., Hopkins, W. G., & Aughey, R. J. (2017). Proposal of a global training load measure predicting match performance in an elite team sport. Frontiers in Physiology, 8, 930. https://doi.org/10.3389/fphys.2017.00930
   PubMed Web of Science ®Google Scholar
• Lovell, T. W., Sirotic, A. C., Impellizzeri, F. M., & Coutts, A. J. (2013). Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. International Journal of Sports Physiology & Performance, 8(1), 62–69. https://doi.org/10.1123/ijspp.8.1.62
   PubMed Web of Science ®Google Scholar
• Lu, D., Howle, K., Waterson, A., Duncan, C., & Duffield, R. (2017). Workload profiles prior to injury in professional soccer players. Science and Medicine in Football, 1(3), 237–243. https://doi.org/10.1080/24733938.2017.1339120
   Web of Science ®Google Scholar
• Malone, J. J., DiMichele, R., Morgans, R., Burgess, D., Morton, J. P., & Drust, B. (2015). Seasonal training-load quantification in elite English premier league soccer players. International Journal of Sports Physiology & Performance, 10(4), 489–497. https://doi.org/10.1123/ijspp.2014-0352
   PubMed Web of Science ®Google Scholar
• Malone, S., Doran, D., Akubat, I., & Collins, K. (2016). The Integration of internal and external training load metrics in hurling. Journal of Human Kinetics, 53(1), 211–221. https://doi.org/10.1515/hukin-2016-0024
   PubMed Web of Science ®Google Scholar
• Malone, S., Owen, A., Mendes, B., Hughes, B., Collins, K., & Gabbett, T. J. (2018). High-speed running and sprinting as an injury risk factor in soccer: Can well-developed physical qualities reduce the risk? Journal of Science & Medicine in Sport / Sports Medicine Australia, 21(3), 257–262. https://doi.org/10.1016/j.jsams.2017.05.016
   PubMed Web of Science ®Google Scholar
• Malone, S., Owen, A., Newton, M., Mendes, B., Collins, K. D., & Gabbett, T. J. (2017). The acute: Chonic workload ratio in relation to injury risk in professional soccer. Journal of Science & Medicine in Sport / Sports Medicine Australia, 20(6), 561–565. https://doi.org/10.1016/j.jsams.2016.10.014
   PubMed Web of Science ®Google Scholar
• Malone, S., Owen, A., Newton, M., Mendes, B., Tiernan, L., Hughes, B., & Collins, K. (2018). Wellbeing perception and the impact on external training output among elite soccer players. Journal of Science & Medicine in Sport / Sports Medicine Australia, 21(1), 29–34. https://doi.org/10.1016/j.jsams.2017.03.019
   PubMed Web of Science ®Google Scholar
• Martín-López, Á., Mendes, R. S., & Castillo-Rodríguez, A. (2021). Internal and external loads in training week before the competition in U19 high-level soccer players. Journal of Strength & Conditioning Research, 35(6), 1766–1772. https://doi.org/10.1519/jsc.0000000000002975
   PubMed Web of Science ®Google Scholar
• Marynowicz, J., Kikut, K., Lango, M., Horna, D., & Andrzejewski, M. (2020). Relationship between the session-RPE and external measures of training load in youth soccer training. Journal of Strength & Conditioning Research, 34(10), 2800–2804. https://doi.org/10.1519/jsc.0000000000003785
   PubMed Web of Science ®Google Scholar
• Maughan, P. C., MacFarlane, N. G., & Swinton, P. A. (2021). Relationship between subjective and external training load variables in youth soccer players. International Journal of Sports Physiology & Performance, 16(8), 1–7. https://doi.org/10.1123/ijspp.2019-0956
   PubMed Web of Science ®Google Scholar
• Maughan, P., Swinton, P., & MacFarlane, N. (2020). Relationships between training load variables in professional youth football players. International Journal of Sports Medicine, 42(7), 624–629. https://doi.org/10.1055/a-1300-2959
   PubMedGoogle Scholar
• McCall, A., Dupont, G., & Ekstrand, J. (2018). Internal workload and non-contact injury: A one-season study of five teams from the UEFA elite club injury study. British Journal of Sports Medicine, 52(23), 1517–1522. https://doi.org/10.1136/bjsports-2017-098473
   PubMed Web of Science ®Google Scholar
• McCall, A., Jones, M., Gelis, L., Duncan, C., Ehrmann, F., Dupont, G., & Duffield, R. (2018). Monitoring loads and non-contact injury during the transition from club to national team prior to an international football tournament: A case study of the 2014 FIFA World cup and 2015 Asia cup. Journal of Science & Medicine in Sport / Sports Medicine Australia, 21(8), 800–804. https://doi.org/10.1016/j.jsams.2017.12.002
   PubMed Web of Science ®Google Scholar
• McLaren, S. J., Macpherson, T. W., Coutts, A. J., Hurst, C., Spears, I. R., & Weston, M. (2018). The relationships between internal and external measures of training load and intensity in team Sports: A meta-analysis. Sports Medicine, 48(3), 641–658. https://doi.org/10.1007/s40279-017-0830-z
   PubMed Web of Science ®Google Scholar
• Miguel, M., Oliveira, R., Loureiro, N., García-Rubio, J., & Ibáñez, S. J. (2021). Load measures in training/match monitoring in soccer: A systematic review. International Journal of Environmental Research and Public Health, 18(5), 2721. https://doi.org/10.3390/ijerph18052721
   PubMed Web of Science ®Google Scholar
• Montini, M., & Rocchi, J. E. (2020). Monitoring training load in soccer: The ROMEI model. Journal of Strength & Conditioning Research, 36(9), 2566–2572. https://doi.org/10.1519/jsc.0000000000003875
   PubMed Web of Science ®Google Scholar
• Nassis, G. P., Verhagen, E., Brito, J., Figueiredo, P., & Krustrup, P. (2023). A review of machine learning applications in soccer with an emphasis on injury risk. Biology of Sport / Institute of Sport, 40(1), 233–239. https://doi.org/10.5114/biolsport.2023.114283
   PubMed Web of Science ®Google Scholar
• Nobari, H., Aquino, R., Clemente, F. M., Khalafi, M., Adsuar, J. C., & Pérez-Gómez, J. (2020). Description of acute and chronic load, training monotony and strain over a season and its relationships with well-being status: A study in elite under-16 soccer players. Physiology & Behavior, 225, 113117. https://doi.org/10.1016/j.physbeh.2020.113117
   PubMed Web of Science ®Google Scholar
• Nobari, H., Praça, G. M., Clemente, F. M., Pérez-Gómez, J., Carlos Vivas, J., & Ahmadi, M. (2020). Comparisons of new body load and metabolic power average workload indices between starters and non-starters: A full-season study in professional soccer players. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering & Technology, 235(2), 105–113. https://doi.org/10.1177/1754337120974873
   Web of Science ®Google Scholar
• Oliveira, R., Brito, J. P., Loureiro, N., Padinha, V., Ferreira, B., & Mendes, B. (2020). Does the distribution of the weekly training load account for the match results of elite professional soccer players? Physiology & Behavior, 225, 113118. https://doi.org/10.1016/j.physbeh.2020.113118
   PubMed Web of Science ®Google Scholar
• Oliveira, R., Brito, J., Martins, A., Mendes, B., Calvete, F., Carriço, S., Ferraz, R., and Marques, M. C. (2019). In-season training load quantification of one-, two- and three-game week schedules in a top European professional soccer team. Physiology & Behavior, 201, 146–156. https://doi.org/10.1016/j.physbeh.2018.11.036
   PubMed Web of Science ®Google Scholar
• Oliveira, R., Brito, J. P., Martins, A., Mendes, B., Marinho, D. A., Ferraz, R., Marques, M. C., & Clemente, F. M. (2019). In-season internal and external training load quantification of an elite European soccer team. PLoS One, 14(4), e0209393. https://doi.org/10.1371/journal.pone.0209393
   PubMed Web of Science ®Google Scholar
• Oliver, J. L., Ayala, F., De Ste Croix, M. B. A., Lloyd, R. S., Myer, G. D., & Read, P. J. (2020). Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players. Journal of Science & Medicine in Sport / Sports Medicine Australia, 23(11), 1044–1048. https://doi.org/10.1016/j.jsams.2020.04.021
   PubMed Web of Science ®Google Scholar
• Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
   PubMed Web of Science ®Google Scholar
• Rago, V., Brito, J., Figueiredo, P., Costa, J., Barreira, D., Krustrup, P., & Rebelo, A. (2020). Methods to collect and interpret external training load using microtechnology incorporating GPS in professional football: A systematic review. Research in Sports Medicine, 28(3), 437–458. https://doi.org/10.1080/15438627.2019.1686703
   PubMed Web of Science ®Google Scholar
• Rago, V., Brito, J., Figueiredo, P., Costa, J., Krustrup, P., & Rebelo, A. (2020). Internal training load monitoring in professional football: A systematic review of methods using rating of perceived exertion. The Journal of Sports Medicine and Physical Fitness, 60(1), 160–171. https://doi.org/10.23736/s0022-4707.19.10000-x
   PubMed Web of Science ®Google Scholar
• Rago, V., Brito, J., Figueiredo, P., Krustrup, P., & Rebelo, A. (2019). Relationship between external load and perceptual responses to training in professional football: Effects of quantification method. Sports, 7(3), 68. https://doi.org/10.3390/sports7030068
   Web of Science ®Google Scholar
• Raya-González, J., Nakamura, F. Y., Castillo, D., Yanci, J., & Fanchini, M. (2019). Determining the relationship between internal load markers and Noncontact injuries in young elite soccer players. International Journal of Sports Physiology & Performance, 14(4), 421–425. https://doi.org/10.1123/ijspp.2018-0466
   PubMed Web of Science ®Google Scholar
• Rebelo, A., Brito, J., Seabra, A., Oliveira, J., Drust, B., & Krustrup, P. (2012). A new tool to measure training load in soccer training and match play. International Journal of Sports Medicine, 33(4), 297–304. https://doi.org/10.1055/s-0031-1297952
   PubMed Web of Science ®Google Scholar
• Reinhardt, L., Schulze, S., Schwesig, R., & Kurz, E. (2020). Physical match performance in sub-elite soccer players - Introduction of a new index. International Journal of Sports Medicine, 41(12), 858–866. https://doi.org/10.1055/a-1165-1950
   PubMed Web of Science ®Google Scholar
• Rico-Gonzalez, M., Pino-Ortega, J., Mendez, A., Clemente, F. M., & Baca, A. (2023). Machine learning application in soccer: A systematic review. Biology of Sport / Institute of Sport, 40(1), 249–263. https://doi.org/10.5114/biolsport.2023.112970
   PubMed Web of Science ®Google Scholar
• Rommers, N., Rössler, R., Verhagen, E., Vandecasteele, F., Verstockt, S., Vaeyens, R., Lenoir, M., D'Hondt, E., and Witvrouw, E. (2020). A Machine learning approach to assess injury risk in elite youth football players. Medicine & Science in Sports and Exercise, 52(8), 1745–1751. https://doi.org/10.1249/mss.0000000000002305
   PubMed Web of Science ®Google Scholar
• Rosenblad, A. J. I. S. R. (2009). Introduction to meta‐analysis by Michael Borenstein, Larry V. Hedges, Julian PT Higgins, Hannah R. Rothstein. International Statistical Review, 77(3), 478–479. https://doi.org/10.1111/j.1751-5823.2009.00095_15.x
   Google Scholar
• Rossi, A., Pappalardo, L., Cintia, P., Iaia, F. M., Fernàndez, J., Medina, D., & Sampaio, J. (2018). Effective injury forecasting in soccer with GPS training data and machine learning. PLoS One, 13(7), e0201264. https://doi.org/10.1371/journal.pone.0201264
   PubMed Web of Science ®Google Scholar
• Rossi, A., Perri, E., Pappalardo, L., Cintia, P., & Iaia, F. M. (2019). Relationship between external and internal workloads in elite soccer players: Comparison between rate of perceived exertion and training load. Applied Sciences, 9(23), 5174. https://doi.org/10.3390/app9235174
   Google Scholar
• Scott, T. J., Black, C. R., Quinn, J., & Coutts, A. J. (2013). Validity and reliability of the session-RPE method for quantifying training in Australian football: A comparison of the CR10 and CR100 scales. Journal of Strength & Conditioning Research, 27(1), 270–276. https://doi.org/10.1519/JSC.0b013e3182541d2e
   PubMed Web of Science ®Google Scholar
• Scott, B. R., Lockie, R. G., Knight, T. J., Clark, A. C., & Janse de Jonge, X. A. (2013). A comparison of methods to quantify the in-season training load of professional soccer players. International Journal of Sports Physiology & Performance, 8(2), 195–202. https://doi.org/10.1123/ijspp.8.2.195
   PubMed Web of Science ®Google Scholar
• Sedeaud, A., De Larochelambert, Q., Moussa, I., Brasse, D., Berrou, J. M., Duncombe, S., Antero, J., Orhant, E., Carling, C., and Toussaint, J. F. (2020). Does an optimal relationship between injury risk and workload represented by the “sweet spot” really exist? An example from elite French soccer players and pentathletes. Frontiers in Physiology, 11, 1034. https://doi.org/10.3389/fphys.2020.01034
   PubMed Web of Science ®Google Scholar
• Sigurdson, H., & Chan, J. H. (2021). Machine learning applications to Sports injury: A review. Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (Icsports), 157–168. https://doi.org/10.5220/0010717100003059
   Google Scholar
• Silva, P., Santos, E. D., Grishin, M., & Rocha, J. M. (2018). Validity of heart rate-based indices to measure training load and intensity in elite football players. Journal of Strength & Conditioning Research, 32(8), 2340–2347. https://doi.org/10.1519/jsc.0000000000002057
   PubMed Web of Science ®Google Scholar
• Strnad, D., Nerat, A., & Kohek, Š. (2017). Neural network models for group behavior prediction: A case of soccer match attendance. Neural Computing and Applications, 28(2), 287–300. https://doi.org/10.1007/s00521-015-2056-z
   Web of Science ®Google Scholar
• Suarez-Arrones, L., De Alba, B., Röll, M., Torreno, I., Strütt, S., Freyler, K., & Ritzmann, R. (2020). Player monitoring in professional soccer: Spikes in acute: Chronic workload are dissociated from injury occurrence. Frontiers in Sports and Active Living, 2, 75. https://doi.org/10.3389/fspor.2020.00075
   PubMedGoogle Scholar
• Suarez-Arrones, L., Torreño, N., Requena, B., Sáez De Villarreal, E., Casamichana, D., Barbero-Alvarez, J. C., & Munguía-Izquierdo, D. (2015). Match-play activity profile in professional soccer players during official games and the relationship between external and internal load. The Journal of Sports Medicine and Physical Fitness, 55(12), 1417–1422.
   PubMed Web of Science ®Google Scholar
• Taylor, R. J., Sanders, D., Myers, T., & Akubat, I. (2020). Reliability and validity of integrated external and internal load ratios as measures of fitness in Academy Rugby Union players. Journal of Strength & Conditioning Research, 34(6), 1723–1730. https://doi.org/10.1519/jsc.0000000000002391
   PubMed Web of Science ®Google Scholar
• Torreño, N., Munguía-Izquierdo, D., Coutts, A., de Villarreal, E. S., Asian-Clemente, J., & Suarez-Arrones, L. (2016). Relationship between external and internal loads of professional soccer players during full matches in official games using global positioning Systems and heart-rate Technology. International Journal of Sports Physiology & Performance, 11(7), 940–946. https://doi.org/10.1123/ijspp.2015-0252
   PubMed Web of Science ®Google Scholar
• Vallance, E., Sutton-Charani, N., Imoussaten, A., Montmain, J., & Perrey, S. (2020). Combining internal-and external-training-loads to predict non-contact injuries in soccer. Applied Sciences, 10(15), 5261. https://doi.org/10.3390/app10155261
   Google Scholar
• Van Eetvelde, H., Mendonca, L. D., Ley, C., Seil, R., & Tischer, T. (2021). Machine learning methods in sport injury prediction and prevention: A systematic review. Journal of Experimental Orthopaedics, 8(1), 27. https://doi.org/10.1186/s40634-021-00346-x
   PubMedGoogle Scholar
• Vanrenterghem, J., Nedergaard, N. J., Robinson, M. A., & Drust, B. (2017). Training load monitoring in team sports: A novel framework separating physiological and biomechanical load-adaptation pathways. Sports Medicine, 47(11), 2135–2142. https://doi.org/10.1007/s40279-017-0714-2
   PubMed Web of Science ®Google Scholar
• Venturelli, M., Schena, F., Zanolla, L., & Bishop, D. (2011). Injury risk factors in young soccer players detected by a multivariate survival model. Journal of Science & Medicine in Sport / Sports Medicine Australia, 14(4), 293–298. https://doi.org/10.1016/j.jsams.2011.02.013
   PubMed Web of Science ®Google Scholar
• Verstappen, S., van Rijn, R. M., Cost, R., & Stubbe, J. H. (2021). The association between training load and injury risk in elite youth soccer players: A systematic review and best evidence synthesis. Sports Medicine - Open, 7(1), 6. https://doi.org/10.1186/s40798-020-00296-1
   PubMedGoogle Scholar
• Viru, A., & Viru, M. (2000). Nature of training effects. In W. E. Garrett & D. T. Kirkendall (Eds.),Exercise and Sport Science (pp. 67–95). Philadelphia: Lippincott Williams & Wilkins.
   Google Scholar
• Wang, M. (2014). Evaluating technical and tactical abilities of football teams in euro 2012 based on improved information entropy model and SOM neural networks. International Journal of Multimedia and Ubiquitous Engineering, 9(11), 293–302. https://doi.org/10.14257/ijmue.2014.9.11.29
   Google Scholar
• Wiig, H., Andersen, T. E., Luteberget, L. S., & Spencer, M. (2020). Individual response to external training load in elite football players. International Journal of Sports Physiology & Performance, 15(5), 696–704. https://doi.org/10.1123/ijspp.2019-0453
   PubMed Web of Science ®Google Scholar