Introducing the technical individual contribution coefficient: a metric for evaluating performance in elite volleyball

References

• Anguera, M., Villaseñor, A., Mendo, H., Antonio, T., & Losada, J. (2011). Observational designs: Their suitability and application in sports psychology. Cuadernos de Psicologia del Deporte, 11, 63–76. https://revistas.um.es/cpd/article/viem/133241
   Google Scholar
• Araújo, R. M., Castro, J., Marcelino, R., & Mesquita, I. R. (2010). Relationship between the opponent block and the hitter in elite male volleyball. Journal of Quantitative Analysis in Sports, 6(4). https://doi.org/10.2202/1559-0410.1216
   Google Scholar
• Araújo, D., Couceiro, M., Seifert, L., Sarmento, H., & Davids, K. (2021). Artificial intelligence in sport performance analysis. Routledge. https://doi.org/10.4324/9781003163589
   Google Scholar
• Basole, R. C., & Saupe, D. (2016). Sports data visualization [guest editors’ introduction]. IEEE Computer Graphics and Applications, 36(5), 24–26. https://doi.org/10.1109/mcg.2016.85
   PubMedGoogle Scholar
• Bisagno, E., Morra, S., Basciano, M., Rosina, C., & Vitali, F. (2019). Assessing individual performance in team sports: A new method developed in youth volleyball. Journal of Functional Morphology and Kinesiology, 4(3), 53. https://doi.org/10.3390/jfmk4030053
   PubMedGoogle Scholar
• Casals, M., & Daunis-I-Estadella, P. (2022). Violinboxplot and enhanced radar plot as components of effective graphical dashboards: An educational example of sports analytics. International Journal of Sports Science & Coaching, 18(2), 572–583. https://doi.org/10.1177/17479541221099638
   Web of Science ®Google Scholar
• Conti, G., Freire, A., Evangelista, B., Pedrosa, G., Ugrinowitsch, H., & Castro, H. (2018). Brazilian high-level men’s volleyball. Kinesiology, 50(2), 211–217. https://doi.org/10.26582/k.50.2.4
   Web of Science ®Google Scholar
• Costa, G. C., Caetano, R. C. J., Ferreira, N. N., Junqueira, G., Afonso, J., Costa, R. D. P., & Mesquita, I. (2011). Determinants of attack tactics in youth male elite volleyball. International Journal of Performance Analysis in Sport, 11(1), 96–104. https://doi.org/10.1080/24748668.2011.11868532
   Web of Science ®Google Scholar
• Cullen, F. T., Myer, A. J., & Latessa, E. J. (2009). Eight lessons from Moneyball: The high cost of ignoring evidence-based corrections. Victims & Offenders, 4(2), 197–213. https://doi.org/10.1080/15564880802612631
   Google Scholar
• Data Volley. (2010) . Data volley system valuation. Statistics and analysis software. Data Project S.L. Italy.
   Google Scholar
• Drikos, S., Barzouka, K., Balasas, D. G., & Sotiropoulos, K. (2021). Effect of quality of opposition on game performance indicators in elite male volleyball. International Journal of Sports Science & Coaching, 17(1), 169–177. https://doi.org/10.1177/17479541211013701
   Web of Science ®Google Scholar
• Drikos, S., & Y Tsoukos, A. (2018). Data benchmarking through a longitudinal study in high-level men’s volleyball. International Journal of Performance Analysis in Sport, 18(3), 470–480. https://doi.org/10.1080/24748668.2018.1493319
   Web of Science ®Google Scholar
• Duch, J., Waitzman, J. S., Amaral, L. A. N., & Scalas, E. (2010). Quantifying the performance of individual players in a team activity. PLoS ONE, 5(6), e10937. https://doi.org/10.1371/journal.pone.0010937
   PubMed Web of Science ®Google Scholar
• Fleiss, J. L. (1986). Design and analysis of clinical experiments. Willey.
   Google Scholar
• Flores-Szwagrzak, K., & Treibich, R. (2020). Teamwork and individual productivity. Management Science, 66(6), 2523–2544. https://doi.org/10.1287/mnsc.2019.3305
   Web of Science ®Google Scholar
• García-Sánchez, I. M. (2007). Efficiency and effectiveness of Spanish football teams: A three-stage-DEA approach. Central European Journal of Research, 15(1), 21–45. https://doi.org/10.1007/s10100-006-0017-4
   Web of Science ®Google Scholar
• Giatsis, G., Drikos, S., & Lola, A. (2022). Analysis of match report indicators in men’s volleyball Olympics and world championships (2014-2021) depending on the type of final score. International Journal of Sports Science & Coaching, 18(3), 874–882. https://doi.org/10.1177/17479541221086779
   Web of Science ®Google Scholar
• Hvattum, L. M. (2019). A comprehensive review of plus-minus ratings for evaluating individual players in team sports. International Journal of Computer Science in Sport, 18(1), 1–23. https://doi.org/10.2478/ijcss-2019-0001
   Google Scholar
• Kizielewicz, B., & Dobryakova, L. (2020). MCDA based approach to sports players’ evaluation under incomplete knowledge. Procedia Computer Science, 176, 3524–3535. https://doi.org/10.1016/j.procs.2020.09.034
   Google Scholar
• Krippendorff, K. (2004). Reliability in content analysis: Some common misconceptions and recommendations. Human Communication Research, 30(3), 411–433. https://doi.org/10.1093/hcr/30.3.411
   Web of Science ®Google Scholar
• Kubatko, J., Oliver, D., Pelton, K., & Rosenbaum, D. T. (2007). A starting point for analyzing basketball statistics. Journal of Quantitative Analysis in Sports, 3(3). https://doi.org/10.2202/1559-0410.1070
   Google Scholar
• Laios, Y., & Kountouris, P. (2005). Evolution in men’s volleyball skills and tactics as evidenced in the Athens 2004 Olympic Games. International Journal of Performance Analysis in Sport, 5(2), 1–8. https://doi.org/10.1080/24748668.2005.11868322
   Google Scholar
• Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
   PubMed Web of Science ®Google Scholar
• Laporta, L., Valongo, B., Afonso, J., & Mesquita, I. (2021). Game-centred study using eigenvector centrality in high-level women’s volleyball: Play efficacy is independent of game patterns … or is it? Montenegrin Journal of Sports Science and Medicine, 10(1), 19–24. https://doi.org/10.26773/mjssm.210303
   Web of Science ®Google Scholar
• Lewis, M. M. (2003). Moneyball: The art of winning an unfair game. W.W. Norton & Company Inc.
   Google Scholar
• Link, D. (2017). Sports analytics. German Journal of Exercise and Sport Research, 48(1), 13–25. https://doi.org/10.1007/s12662-017-0487-7
   Web of Science ®Google Scholar
• López-Serrano, C., Moreno, M. P., Mon-López, D., & Molina-Martín, J. J. (2022). Elite coaches’ approach to quantifying technical actions and relative participation in volleyball players’ performance. Journal of Human Sport & Exercise, 18(2). https://doi.org/10.14198/jhse.2023.182.10
   Web of Science ®Google Scholar
• Lorenzo, J., Lorenzo, A., Conte, D., & Giménez, M. (2019). Long-term analysis of elite basketball players’ game-related statistics throughout their careers. Frontiers in Psychology, 10, 10. https://doi.org/10.3389/fpsyg.2019.00421
   PubMed Web of Science ®Google Scholar
• Marcelino, R., Mesquita, I., & Afonso, J. (2008). The weight of terminal actions in volleyball. Contributions of the spike, serve and block for the teams’ rankings in the World league 2005. International Journal of Performance Analysis in Sport, 8(2), 1–7. https://doi.org/10.1080/24748668.2008.11868430
   Google Scholar
• Mercado-Palomino, E., Millán-Sánchez, A., Parra-Royón, M. J., Benítez, J. M., & Ureña Espa, A. (2022). Rango de acción del colocador como indicador de rendimiento en voleibol masculino. Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte, 22(85), 169–182. https://doi.org/10.15366/rimcafd2022.85.011
   Google Scholar
• Millán-Sánchez, A., Morante Rábago, C. J., Álvarez, M., Fernia, P., & Ureña, A. (2015). Participation in terminal actions according to the role of the player and his location on the court in top-level men’s volleyball. International Journal of Performance Analysis in Sport, 15(2), 608–619. https://doi.org/10.1080/24748668.2015.11868818
   Web of Science ®Google Scholar
• Millán-Sánchez, A., Parra-Royón, M. J., Benítez, J. M., & Ureña Espa, A. (2020). Ability to predict side-out performance by the setter’s action range with first tempo availability in top European male and female teams. International Journal of Environmental Research and Public Health, 17(17), 6326. https://doi.org/10.3390/ijerph17176326
   PubMed Web of Science ®Google Scholar
• Monteiro, R., Mesquita, I., & Marcelino, R. (2009). Relationship between the set outcome and the dig and attack efficacy in elite male volleyball game. International Journal of Performance Analysis in Sport, 9(3), 294–305. https://doi.org/10.1080/24748668.2009.11868486
   Google Scholar
• Mortenson, M. J., Doherty, N. F., & Robinson, S. (2015). Operational research from taylorism to terabytes: A research agenda for the analytics age. European Journal of Operational Research, 241(3), 583–595. https://doi.org/10.1016/j.ejor.2014.08.029
   Web of Science ®Google Scholar
• Nikos, B., Karolina, B., & Elissavet, N. M. (2009). Performance of male and female setters and attackers on Olympic-level volleyball teams. International Journal of Performance Analysis in Sport, 9(1), 141–148. https://doi.org/10.1080/24748668.2009.11868470
   Google Scholar
• Palao, J. M., & Hernández-Hernández, E. (2014). Game statistical system and criteria used by Spanish volleyball coaches. International Journal of Performance Analysis in Sport, 14(2), 564–573. https://doi.org/10.1080/24748668.2014.11868743
   Web of Science ®Google Scholar
• Palao, J. M., Manzanares López, P., & Ortega, E. (2015). Design and validation of an observational instrument for technical and tactical actions in beach volleyball. Motriz: Revista de Educação Física, 21(2), 137–147. https://doi.org/10.1590/s1980-65742015000200004
   Google Scholar
• Palao, J. M., Manzanares, P., & Ortega, E. (2009). Techniques used and efficacy of volleyball skills in relation to gender. International Journal of Performance Analysis in Sport, 9(2), 281–293. https://doi.org/10.1080/24748668.2009.11868484
   Google Scholar
• Papadimitriou, K., Pashali, E., Sermaki, I., Mellas, S., & Papas, M. (2004). The effect of the opponents’ serve on the offensive actions of Greek setters in volleyball games. International Journal of Performance Analysis in Sport, 4(1), 23–33. https://doi.org/10.1080/24748668.2004.11868288
   Google Scholar
• Ramírez-López, C., Till, K., Boyd, A., Bennet, M., Piscione, J., Bradley, S., Giuliano, P., Leduc, C., & Jones, B. (2020). Coopetition: Cooperation among competitors to enhance applied research and drive innovation in elite sport. British Journal of Sports Medicine, 55(10), 522–523. https://doi.org/10.1136/bjsports-2020-102901
   Web of Science ®Google Scholar
• Silva, M., Sattler, T., Lacerda, D., & João, P. V. (2016). Match analysis according to the performance of team rotations in volleyball. International Journal of Performance Analysis in Sport, 16(3), 1076–1086. https://doi.org/10.1080/24748668.2016.11868949
   Web of Science ®Google Scholar
• Vilar, L., Araújo, D., Davids, K., & Button, C. (2012). The role of ecological dynamics in analysing performance in team sports. Sports Medicine, 42(1), 1–10. https://doi.org/10.2165/11596520-000000000-00000
   PubMed Web of Science ®Google Scholar
• Zetou, E., Moustakidis, A., Tsigilis, N., & Komninakidou, A. (2007). Does effectiveness of skill in complex I predict win in men’s Olympic volleyball games? Journal of Quantitative Analysis in Sports, 3(4). https://doi.org/10.2202/1559-0410.1076
   Google Scholar
• Zidane, Y. J. T., & Olsson, N. O. E. (2017). Defining project efficiency, effectiveness and efficacy. International Journal of Managing Projects in Business, 10(3), 621–641. https://doi.org/10.1108/ijmpb-10-2016-0085
   Web of Science ®Google Scholar