Hybrid Recommendation System for Young Football Athletes Customized Training

  • Paulo MatosEmail author
  • João Rocha
  • Ramiro Gonçalves
  • Filipe Santos
  • David Abreu
  • Hugo Soares
  • Constantino Martins
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1129)


Information and communication technologies (ICTs) are been increasingly used in sports over the past decades, especially in professional football, with the goal of enhancing preparation and improve the athletes’ performance. Training programs, however, are not accessible for young and amateur athletes. Most of the systems available, don’t have learning skills to adjust, develop and find new suggestions for training, specifically designed for each athlete. In this paper we present the Smart Coach architecture and user adaptation model and describe our hybrid recommendation system to help the development of young athletes. It simplifies the relationship between the team’s technical staff leaders and their young athletes, enhancing the counselling of the young person and their development as an athlete. The system allows performance evaluation for young athletes utilizing various measurements. The match information is captured intuitively and adaptively by acquaintances, relatives and staff, using a comfortable smartphone interface.


Recommender systems User modelling Personalized coaching Reasoning 



This work was supported by National Funds through the FCT—Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) Project UID/EEA/00760/2019 and by FLAD—Fundação Luso-Americana para o Desenvolvimento (Luso-American Development Foundation) Project 52/2020.


  1. 1.
    Anderberg, M.R.: Cluster analysis for applications. Technical report, Office of the Assistant for Study Support Kirtland AFB N MEX (1973)Google Scholar
  2. 2.
    Barab, S., Squire, K.: Design-based research: putting a stake in the ground. J. Learn. Sci. 13(1), 1–14 (2004)CrossRefGoogle Scholar
  3. 3.
    Berka, T., Plößnig, M.: Designing recommender systems for tourism. In: Proceedings of ENTER 2004, pp. 26–28 (2004)Google Scholar
  4. 4.
    Cheong, C., Cheong, F., Filippou, J.: Using design science research to incorporate gamification into learning activities. In: PACIS, p. 156 (2013)Google Scholar
  5. 5.
    Dossier do treinador de football (2018).
  6. 6.
    Felfernig, A., Gordea, S., Jannach, D., Teppan, E., Zanker, M.: A short survey of recommendation technologies in travel and tourism. OEGAI J. 25(7), 17–22 (2007)Google Scholar
  7. 7.
    Kabassi, K.: Personalizing recommendations for tourists. Telematics Inform. 27(1), 51–66 (2010)CrossRefGoogle Scholar
  8. 8.
    Kobsa, A.: User modeling: recent work, prospects and hazards. Hum. Factors Inf. Technol. 10, 111–111 (1993)Google Scholar
  9. 9.
    Kobsa, A.: Generic user modeling systems. User Model. User-Adap. Inter. 11(1–2), 49–63 (2001)CrossRefGoogle Scholar
  10. 10.
    Martins, C., Faria, L., Carvalho, C.V.D., Carrapatoso, E.: User modeling in adaptive hypermedia educational systems. Educ. Technol. Soc. 11(1), 194–207 (2008)Google Scholar
  11. 11.
    Matos, P., Rocha, J., Gonçalves, R., Almeida, A., Santos, F., Abreu, D., Martins, C.: Smart coach–a recommendation system for young football athletes. In: Novais, P., Lloret, J., Chamoso, P., Carneiro, D., Navarro, E., Omatu, S. (eds.) Ambient Intelligence - Software and Applications,10th International Symposium on Ambient Intelligence. Advances in Intelligent Systems and Computing, vol. 1006, pp. 171–178. Springer, Cham (2019)CrossRefGoogle Scholar
  12. 12.
    My coach football - the digital assistant for educators (2018).
  13. 13.
    Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manage. Inf. Syst. 24(3), 45–77 (2007)CrossRefGoogle Scholar
  14. 14.
    Porter, J.: Watch and learn: how recommendation systems are redefining the web, May 2006. Accessed 01 Feb 2019
  15. 15.
    Rich, E.: User modeling via stereotypes. Cogn. Sci. 3(4), 329–354 (1979)CrossRefGoogle Scholar
  16. 16.
    Santos, F., Almeida, A., Martins, C., Gonçalves, R., Martins, J.: Using POI functionality and accessibility levels for delivering personalized tourism recommendations. Comput. Environ. Urban Syst. 77, 101173 (2019)CrossRefGoogle Scholar
  17. 17.
    Santos, F., Almeida, A., Martins, C., Oliveira, P., Gonçalves, R.: Tourism recommendation system based in user functionality and points-of-interest accessibility levels. In: Mejia, J., Mirna, M., Rocha, Á., San Feliu, T., Peña, A. (eds.) Trends and Applications in Software Engineering, pp. 275–284. Springer, Cham (2017)CrossRefGoogle Scholar
  18. 18.
    Schafer, J.B., Konstan, J., Riedl, J.: Recommender systems in E-commerce. In: Proceedings of the 1st ACM Conference on Electronic Commerce, pp. 158–166. ACM (1999)Google Scholar
  19. 19.
    Soccer coach | the definitive coaching app (2018).
  20. 20.
    Online sports team management software - sporteasy (2018).
  21. 21.
    Tactical soccer - complete suite for soccer coaches (2018).
  22. 22.
    Van den Akker, J., Gravemeijer, K., McKenney, S., Nieveen, N.: Educational Design Research. Routledge, London (2006)CrossRefGoogle Scholar
  23. 23.
    Woodward, C.A., Chambers, L.W.: Guide to Questionnaire Construction and Question Writing. Canadian Public Health Association, Ottawa (1983)Google Scholar
  24. 24.
    Zukerman, I., Albrecht, D.W.: Predictive statistical models for user modeling. User Model. User-Adap. Inter. 11(1–2), 5–18 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Paulo Matos
    • 1
    • 3
    Email author
  • João Rocha
    • 1
  • Ramiro Gonçalves
    • 2
    • 4
  • Filipe Santos
    • 1
    • 3
  • David Abreu
    • 1
  • Hugo Soares
    • 1
  • Constantino Martins
    • 1
    • 3
  1. 1.Computer Science DepartmentEngineering Institute - Polytechnic of PortoPortoPortugal
  2. 2.Trás-os-Montes e Alto Douro UniversityVila RealPortugal
  3. 3.GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and DevelopmentPortoPortugal
  4. 4.INESC TEC - Institute for Systems and Computer Engineering, Technology and SciencePortoPortugal

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