SIGNIFICANCE OF DISCRIMINANT ANALYSIS FOR CLASSIFICATION AND TALENT IDENTIFICATION IN SPORTS – A THEMATIC REVIEW
DOI:
https://doi.org/10.29121/shodhkosh.v5.i4.2024.5752Keywords:
Talent Identification, Discriminant Analysis, SportsAbstract [English]
Talent identification, crucial in sports, education, and employment, utilizes Multiple Discriminant Analysis (MDA) to assess various predictor variables for talent levels. MDA helps pinpoint factors correlated with success, such as physical attributes, skills, and psychological traits, aiding in tailored training and team selection. In sports, MDA serves to identify critical combinations of attributes, distinguish elite athletes, spot potential talent early, and tailor talent identification models to different sports. While widely used, MDA's effectiveness across diverse sports disciplines remains underexplored, with gaps in understanding its applicability and reliability in different contexts. Further research is needed to determine how well MDA discriminates between athletes in sports with varied demands and to select appropriate variables for different sports. This review underscores the importance of MDA in talent identification and calls for more focused studies to enhance its application and effectiveness in sports contexts.
References
A. W. S. Watson (1988) Discriminant analysis of the physiques of schoolboy rugby players, hurlers and non‐team members, Journal of Sports Sciences, 6:2, 131-140, DOI: 10.1080/02640418808729803 DOI: https://doi.org/10.1080/02640418808729803
Barış Ergül, Arzu Altın Yavuz & Hasan Serhan Yavuz. Classification of NBA League Teams Using Discriminant and Logistic Regression Analyses. Pamukkale Journal of Sport Sciences 2014, Vol.5, No.1, Pg:48-60
Betz, N. E. (1987). Use of discriminant analysis in counseling psychology research. Journal of Counseling Psychology, 34(4), 393-403. DOI: https://doi.org/10.1037//0022-0167.34.4.393
Bianca Miarka, H. David Fukuda, Fabrício B. Del Vecchio & Emerson Franchini (2016) Discriminant analysis of technical-tactical actions in high-level judo athletes, International Journal of Performance Analysis in Sport, 16:1, 30-39 DOI: https://doi.org/10.1080/24748668.2016.11868868
Borgen, F. H., & Seling, M. J. (1978). Uses of discriminant analysis following MANOVA: Multivariate statistics for multivariate purposes. Journal of Applied Psychology, 63, 689-697. DOI: https://doi.org/10.1037//0021-9010.63.6.689
Bray, J. H., & Maxwell, S. E. (1982). Analyzing and interpreting significant MANOVA's. Review of Educational Research, 52, 340-367. DOI: https://doi.org/10.3102/00346543052003340
Brown, M. T., & Tinsley, H. E. A. (1983). Discriminant analysis. Journal of Leisure Research, 15(4), 290-310. DOI: https://doi.org/10.1080/00222216.1983.11969564
Carlos Lago-Peñas, Joaquín Lago-Ballesteros, Ezequiel Rey. Differences in performance indicators between winning and losing teams in the UEFA Champions League. Journal of Human Kinetics volume 27/2011, 135-146 Section III – Sport, Physical Education & Recreation DOI: 10.2478/v10078-011-0011-3 135 DOI: https://doi.org/10.2478/v10078-011-0011-3
Cocozzelli, C. (1988). Understanding canonical discriminant function analysis: Testing typological hypotheses. Journal of Social Service Research, 11(2/3), 93-117. DOI: https://doi.org/10.1300/J079v11n02_06
Dixon, W. J. (Ed.). (1992). BMDP statistical software manual: The data manager~to accompany release 7~version 7.0, Vol. 3. Berkeley: Unversity of California Press.
Dumont, E. R. (1997). Cranial shape in fruit, nectar, and exudate feeders: Implications for interpreting the fossil record. American Journal of Anthropology, 102, 187-202. DOI: https://doi.org/10.1002/(SICI)1096-8644(199702)102:2<187::AID-AJPA4>3.3.CO;2-W
Faber, I R., Sloot, L., Hoogeveen, L., Elferink-Gemser, M T., & Schorer, J. (2021, March 31). Western Approaches for the identification and development of talent in schools and sports contexts from 2009 to 2019 - a literature review. https://www.tandfonline.com/doi/full/10.1080/13598139.2021.1900792 DOI: https://doi.org/10.1080/13598139.2021.1900792
Huberty, C. J. (1975). Discriminant analysis. Review of Educational Research, 45, 543-598. DOI: https://doi.org/10.3102/00346543045004543
Huberty, C. J. (1994). Why multivariable analyses? Educational and Psychological Measurement, 54 (3), 620-627. DOI: https://doi.org/10.1177/0013164494054003005
IVASHCHENKO O.V., YERMAKOVA T.S., CIESLICKA M., MUSZKIETA R. Discriminant analysis as method of pedagogic control of 9-11 forms girls’ functional and motor fitness. Journal of Physical Education and Sport ® (JPES), 15(3), Art 86 pp.576 - 581, 2015
Jaime Sampaio, Manuel Janeira, Sergio Ibáñez & Alberto Lorenzo (2006): Discriminant analysis of game-related statistics between basketball guards, forwards and centres in three professional leagues, European Journal of Sport Science, 6:3, 173-178 DOI: https://doi.org/10.1080/17461390600676200
Katrijn Opstoel, Johan Pion, Marije Elferink-Gemser, Esther Hartman, Bas Willemse, Renaat Philippaerts, Chris Visscher, Matthieu Lenoir. Anthropometric Characteristics, Physical Fitness and Motor Coordination of 9 to 11 Year Old Children Participating in a Wide Range of Sports. PLoS ONE 10(5) 2015: e0126282. doi:10.1371/journal.pone.0126282 DOI: https://doi.org/10.1371/journal.pone.0126282
Klecka, W. R. (1975). Discriminant analysis. In N. H. Nie, C. H. Hull, J. G. Jenkins, K.
Kruhlov, V., & Khudolii, O. (2022). Discriminant Analysis: Age-Specific Features of Motor Fitness of Girls Aged 7 to 9. Physical Education Theory and Methodology. DOI: 10.17309/tmfv.2022.3s.20 DOI: https://doi.org/10.17309/tmfv.2022.3s.20
Lidor, R., Côté, J., & Hackfort, D. (2009, January 1). ISSP position stand: To test or not to test? The use of physical skill tests in talent detection and in early phases of sport development. International journal of sport and exercise psychology, 7(2), 131-146. https://doi.org/10.1080/1612197x.2009.9671896 DOI: https://doi.org/10.1080/1612197X.2009.9671896
Mario Leone, Georges Lariviere & Alain S. Comtois (2002) Discriminant analysis of anthropometric and biomotor variables among elite adolescent female athletes in four sports, Journal of Sports Sciences, 20:6, 443-449, DOI: 10.1080/02640410252925116 DOI: https://doi.org/10.1080/02640410252925116
Michael L. Pollock , Andrew S. Jackson & Russell R. Pate (1980) Discriminant Analysis of Physiological Differences Between Good and Elite Distance Runners, Research Quarterly for Exercise and Sport, 51:3, 521-532, DOI:10.1080/02701367.1980.10608075 DOI: https://doi.org/10.1080/02701367.1980.10608075
Morrison, D. G. (1974). Discriminant analysis. In R. Ferber (Ed.), Handbook of marketing research. New York: McGraw-Hill.
Norusis, M. J. (1990). SPSS advanced statistics user's guide. Chicago, IL: SPSS.
Norusis, M. J., & Norusis, M. J. (1998). SPSS 8.0 guide to data analysis. Chicago: SPSS.
Oloo Micky Olutende, Jasper Situma Wekesa, Edinah Sabiri Mogaka, Issah Wabuyabo Kweyu DISCRIMINANT ANALYSIS OF ANTHROPOMETRIC AND BIOMOTOR VARIABLES AMONG GROUPS OF MALE UNIVERSITY ATHLETES IN THREE SPORTS. European Journal of Physical Education and Sport Science. Volume 4, Issue 12, 2018
Patsiaouras Asterios, Charitonidis Kostantinos, Moustakidis Athanasios & Kokaridas Dimitrios (2009) Comparison of technical skills effectiveness of men’s National Volleyball teams, International Journal of Performance Analysis in Sport, 9:1, 1-7 dx.doi.org/10.1080/24748668.2009.11868460. DOI: https://doi.org/10.1080/24748668.2009.11868460
Richard M. Smith & Warwick L. Spinks (1995) Discriminant analysis of biomechanical differences between novice, good and elite rowers, Journal of Sports Sciences, 13:5, 377-385, DOI: 10.1080/02640419508732253 DOI: https://doi.org/10.1080/02640419508732253
Shaoliang Zhang, Alberto Lorenzo, Miguel-Angel Gómez, Nuno Mateus, Bruno Gonçalves & Jaime Sampaio (2018): Clustering performances in the NBA according to players’ anthropometric attributes and playing experience, Journal of Sports Sciences. doi.org/10.1080/02640414.2018.1466493 DOI: https://doi.org/10.1080/02640414.2018.1466493
Stahmann, R F., & Wallen, N E. (1966, July 1). Multiple Discriminant Prediction of Major Field of Study. Educational and psychological measurement, 26(2), 439-444. https://doi.org/10.1177/001316446602600218 DOI: https://doi.org/10.1177/001316446602600218
Steinbrenner, & D. H. Bent (Eds.), Statistical package for the social sciences (2nd ed., pp. 434-467). New York: McGraw-Hill.
Thuany, M.; Souza, R.F.d.; Hill, L.; Mesquita, J.L.; Rosemann, T.; Knechtle, B.; Pereira, S.; Gomes, T.N. Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels. Int. J. Environ. Res. Public Health 2021, 18, 4248. https://doi.org/10.3390/ijerph18084248 DOI: https://doi.org/10.3390/ijerph18084248
Verma, J.P. Data Analysis in Management with SPSS software. Springer, 2009
Verma, J.P., Modak, Pintu, Bhukar, J.P., Kumar, Sanjeev. A discriminant analysis of team cohesiveness among high-performance and low-performance elite Indian volleyball players. Studies in Physical Culture and Tourism, Volume 19, No 4, 2012, 191-195
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