A Discriminant Model For Skill Oriented Prediction of Female Cricketers Depending Upon Selected Performance Parameters

Keywords: discriminant model, Wilk's lambda, eigenvalue, classification matrix


Research Purpose. The study aimed to develop a discriminant model for cricketers on the basis of physiological & anthropometric variables.

Material and Methods. The study included sixty female seniors BCCI board players representing five different states with mean age 23.4 ± 2.03, mean height 152.1 ± 3.44, and mean weight 52.4 ± 4.21. A multivariate technique was used to predict the cricket performance by classifying the players into batsmen and pace bowlers on the basis of selected physiological & anthropometrical variables.

Results. All the assumptions were positively full-filled (Shapiro-Wilk test p > 0.05 and F = 8.121, p = 0.264 for Box’sM test) for applying discriminant analysis to develop the model. A total of eleven performance variables were initially selected for the study and after applying the stepwise statistical technique of discriminant analysis, the model selected certain variables, namely Muscle Mass (1.311), Fat (-0.182) & Shoulder Diameter (0.292) and showed its effectiveness as the Eigenvalue for the fit model was 0.848.

Conclusion. A discriminant function F1 = -29.531 + (1.311 × Muscle Mass) + (-0.182 × Fat) + (0.292 × Shoulder Diameter) was developed. The percentage of total variation explained by the model was 71.9%. A total of 93.2% of the observations were correctly classified using the proposed discriminant model.


Download data is not yet available.

Author Biographies

Sapna Mandoli, Lakshmibai National Institute of Physical Education

Department of Exercise Physiology,
Shaktinagar, Mela Road, Gwalior, Madhya Pradesh, Pin Code-474002, India

Deepak Sharma, Lakshmibai National Institute of Physical Education

Department of Exercise Physiology,
Shaktinagar, Mela Road, Gwalior, Madhya Pradesh, Pin Code-474002, India

Hem Chandra Joshi, Lakshmibai National Institute of Physical Education

Department of Sports Biomechanics,
Guwahati, Assam, Pin Code-782402, India


Ahamad, G., Naqvi, S. K., & Beg, M. M. S. (2016). An OWA-Based Model for Talent Enhancement in Cricket. International Journal of Intelligent Systems, 31(8), 763-785. https://doi.org/10.1002/int.21802

Peltola, E. (1992). Talent Identification. Sports Psychology Bulletin, 3(5), 10-11.

Williams, A.M. & Reilly, T. (2000). Talent Identification and Development in Soccer. Journal of Sports Sciences, 18(9), 657-667. https://doi.org/10.1080/02640410050120041

Mallillin, T., Collantes, B.E., GO, M.R., Platoon, S.G., & Villegas, R.A. (2007). Sports talent identification in 1st and 2nd year UST high school students. Philippine journal of allied health sciences, 2(1), 41-42. https://doi.org/10.1016/j.procs.2015.08.426

Noakes, T. D., & Durandt, J. J. (2000). Physiological requirements of cricket. Journal of Sports Sciences, 18, 919-929. https://doi.org/10.1080/026404100446739

Hoque, N. (2019). Anthropometric Characteristics and Physiological Fitness Status of Male Cricket Players of Kerala. Journal of Emerging Technologies and Innovative Research, 6(1), 712-718

Johnstone, J.A., Mitchell, A.C., Hughes, G., Watson, T., Ford, P.A., & Garrett, A.T. (2014). The athletic profile of fast bowling in cricket: A review. Journal of Strength and Conditioning Research, 28(5), 1465-1473. https://doi.org/10.1519/JSC.0b013e3182a20f8c

Pyne, D.B., Duthie, G.M., Saunders P.U., Petersen, C.A., & Portus, M. (2006). Anthropometric and strength correlates of fast bowling speed in junior and senior cricketers. Journal of Strength and Conditioning Research, 20(3), 620-626.

Christie, C.A. (2012). The Physical Demands of Batting and Fast Bowling in Cricket, An International Perspective on Topics in Sports Medicine and Sports Injury, Dr. Kenneth R. Zaslav (Ed.), ISBN: 978-953-51-0005-8, InTech.

Rudkin, S.T., & O’Donogue, P.G. (2008). Time motion analysis of first-class cricket fielding. Journal of Science and Medicine in Sport, 11(6), 604-607. https://doi.org/10.1016/j.jsams.2007.08.004

Gore, C.J., Bourdon, P.C., Woolford, S.M., & Pederson, D.G. (1993). Involuntary dehydration during cricket. International Journal of Sports Medicine, 14(7), 387-395. https://doi.org/10.1055/s-2007-1021197

Leone, M., Lariviere, G., & Comtois, A.S. (2002). Discriminant analysis of anthropometric and biomotor variables among elite adolescent female athletes in four sports. Journal of sports sciences, 20(6), 443-9. https://doi.org/10.1080/02640410252925116

Koley, S. (2006). New Horizons in Kinanthropometry. New Delhi: Friends Publications.

Landers, G. J., Blanksby, B. A., Ackland, T. R., & Smith, D. (2000). Morphology and performance of world championship triathletes. Annals of Human Biology, 27(4), 387-400. https://doi.org/10.1080/03014460050044865

Nazeer, M. T., Haq, M. Z. U., & Habib, M. B. (2018). Anthropometric and Physical Fitness of the Under-16 Regional-School Cricket Players, of Bahawalpur, Pakistan. Global Regional Review, Humanity, 3(1), 333-342. https://doi.org/10.31703/grr.2018(III-I).24

Bartlett, R. M. (2003). The science and medicine of cricket: an overview and update. Journal of Sports Sciences, 21(9), 733-752. https://doi.org/10.1080/0264041031000140257

Woolmer, B., Noakes, T., & Moffett, H. (2008). Bob Woolmer’s Art and Science of Cricket (1st ed.). Sydney: New Holland Publishers Ltd.

Stretch, R. A. (1987). Anthropometric profile of first-class cricketers. South African Journal for Research in Sport Physical Education and Recreation, 10(1), 65-75.

Thomas, J.R., Nelson, J.K., & Silverman, S.J. (2011). Research method in Physical Activity (6th ed.). Human Kinetics, 173-175.

Verma, J.P. (2013). Data Analysis in Management with SPSSSoftware (1st ed.). Dordrecht London: Springer, 389-407. https://doi.org/10.1007/978-81-322-0786-3

Tew, J., & Wood, M. (1980). Proposed Model for Predicting Probable Success in Football Players. Houton, TX: Rice University Press.

Bagchi, A., & Raizada, S. (2020). Development of the Discriminant Model for Classifying Cricketers Based on Anthropometric and Physical Variables. Annals of Tropical Medicine and Public Health, 23(17). https://doi.org/10.36295/ASRO.2020.231759

Pollock, M.L., Jackson, A.S., & Pate, R.R. (2013). Discriminant Analysis of Physiological Differences between Good and Elite Distance Runners. Research Quarterly for Exercise and Sport, 51(3), 521-532. https://doi.org/10.1080/02701367.1980.10608075

Pion, J., Segers, V., Fransen, J., Debuyck, G., Deprez, D., Haerens, L., et. al. (2015). Generic anthropometric and performance characteristics among elite adolescent boys in nine different sports. European Journal of Sport Science,15 (5), 357-66. https://doi.org/10.1080/17461391.2014.944875

McArdle, W.D., Katch, F., Pechar, G., Jacobson, L., & Ruck, S. (1972). Reliability and interrelationships between maximal oxygen intake, physical work capacity and step-test scores in college women. Medicine and science in sports, 4(4), 182-186. https://doi.org/10.1249/00005768-197200440-00019

Stretch, R.A., & Buys, F.J. (1991). Anthropometric profile and body composition changes in first-class cricketers. South African Journal for Research in Sport, Physical Education and Recreation, 14(2), 57-64.

Brechue, W., Mayhew, J., & Piper, F.C. (2010). Characteristics of Sprint Performance in College football Players. Journal strength and conditioning, 24(5), 1169-78. https://doi.org/10.1519/JSC.0b013e3181d68107

Gacesa, J. P., Borak, O., Jakovljevic, D.K., Klasnja, A., Galic, V., Drapsin, M. et. al. (2011). Body mass index and body fat content in elite athletes. Exercise and Quality of Life, 3(2), 43-48.

Prado, W.L.D., Botero, J.P., Guerra, R.L.F., Rodrigues, C.L., Cuvello, L.C.F., & Dâmaso, A.R. (2006). Anthropometric profile and macronutrient intake in professional Brazilian soccer players according to their field positioning. Rev Bras Med Esporte, 2(12), 61-65. https://doi.org/10.1590/S1517-86922006000200001

Potteiger, J. A, Smith, D. L, Maier, M. L, & Foster, T. S. (2010). Relationship Between Body Composition, Leg Strength, Anaerobic Power, and On-Ice Skating Performance in Division I Men’s Hockey Athletes. Journal of Strength and Conditioning Research, 24(7), 1755-1762. https://doi.org/10.1519/JSC.0b013e3181e06cfb

Högström, G. M., Pietilä, T., Nordström, P., & Nordström, A. (2012). Body Composition and Performance. Journal of Strength and Conditioning Research, 26(7), 1799-1804. https://doi.org/10.1519/JSC.0b013e318237e8da

Carbuhn, A.F., Fernandez, T.E., Bragg, A.F., Green, J.S., & Crouse, S.F. (2010). Sport and training influence bone and body composition in women collegiate athletes. Journal Strength Conditioning, 24(7), 1710-1717. https://doi.org/10.1519/JSC.0b013e3181d09eb3

Spaniol, F.J., Bonnette, R., Melrose, D., & Bohling, M. (2006). Physiological predictors of bat speed and batted-ball velocity in NCAA Division I baseball players. Journal of Strength Conditioning, 20(4), 20-25. https://doi.org/10.1519/JSC.0b013e3181f0a76a

Basile, R., Otto, R., & Wygand, J. (2007). The relationship between physical and physiological performance measures and baseball performance measures. Medicine Science Sports Exercise, 39(5), 14-21. https://doi.org/10.1249/01.mss.0000273807.89364.04

Bonnette, R., Spaniol, F., Melrose, D., Ocker, L., Paluseo, J., & Szymanski, D. (2008). The relationship between rotational power, bat speed, and batted-ball velocity of NCAA Division I baseball players. Journal of Strength Conditioning, 22, 112-122.
0 article
How to Cite
Mandoli, S., Sharma, D., & Joshi, H. C. (2021). A Discriminant Model For Skill Oriented Prediction of Female Cricketers Depending Upon Selected Performance Parameters. Teorìâ Ta Metodika Fìzičnogo Vihovannâ, 21(4), 293-298. https://doi.org/10.17309/tmfv.2021.4.01