Journals / Gazi Beden Eğitimi ve Spor Bilimleri Dergisi / 2026 / Volume: 31 Issue: 3

A Multidimensional Analysis of Self-Perceived Performance in Competitive Athletes: Psychometric Evaluation and Associations with Athlete Characteristics

Mesut Süleymanoğulları(Ağrı İbrahim Çeçen Üniversitesi)0000-0001-5867-2844
Pages
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Publication Date
2026-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

SAPÖ scores may provisionally complement objective indicators and athlete–practitioner discussion, but not independently determine selection, diagnosis, ranking, or training modification.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Self-perceived athletic performance complements objective indicators by reflecting athletes’ physical, technical, tactical, psychological, and environmental evaluations.
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Key Findings & Data:This cross-sectional study evaluated the internal consistency and factorial validity of the Self-Perceived Performance Scale (SAPÖ) and its associations with athlete characteristics.
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Conclusion & Impact:SAPÖ scores may provisionally complement objective indicators and athlete–practitioner discussion, but not independently determine selection, diagnosis, ranking, or training modification.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Competitive sport · Self-Perceived Performance · Multidimensional Assessment

Abstract

Self-perceived athletic performance complements objective indicators by reflecting athletes’ physical, technical, tactical, psychological, and environmental evaluations. This cross-sectional study evaluated the internal consistency and factorial validity of the Self-Perceived Performance Scale (SAPÖ) and its associations with athlete characteristics. Participants competed in football, karate, judo, volleyball, basketball, or athletics in Türkiye (N = 370; age M = 21.38, SD = 4.30 years; 219 men [59.2%] and 151 women [40.8%]; 272 local-level [73.5%], 48 national-level [13.0%], and 50 international-level [13.5%] athletes; sport experience M = 6.17, SD = 4.03 years). Analyses included Cronbach’s α, McDonald’s ω, WLSMV confirmatory factor analysis, and Type III MANCOVA. Internal consistency was acceptable to good for the subscales (α = .758–.844; ω = .770–.848) and high for the total score (α = .937; ω = .959). Although CFI and TLI were strong (.971 and .967), elevated RMSEA and SRMR values, near-unity latent-factor correlations, and a non-positive definite latent covariance matrix indicated mixed evidence and unresolved structural limitations. Sport discipline, age, and sport experience were associated with the combined SAPÖ profile; sex, competition level (p = .054), and national-team status were not significant. The smallest unadjusted follow-up p values occurred for Physical Perception; without multiplicity control across outcomes, these analyses were exploratory. Scores were internally consistent, but unresolved factorial limitations and the cross-sectional design preclude causal or stand-alone diagnostic interpretation. SAPÖ scores may provisionally complement objective indicators and athlete–practitioner discussion, but not independently determine selection, diagnosis, ranking, or training modification.

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Cite This Article

Süleymanoğulları, M. (2026). A Multidimensional Analysis of Self-Perceived Performance in Competitive Athletes: Psychometric Evaluation and Associations with Athlete Characteristics. Gazi Beden Eğitimi ve Spor Bilimleri Dergisi, Volume: 31 Issue: 3. https://doi.org/10.53434/gbesbd.1993667

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References (30)

  1. Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
  2. Box, G. E. P. (1949). A general distribution theory for a class of likelihood criteria. Biometrika, 36(3–4), 317–346. https://doi.org/10.1093/biomet/36.3-4.317
  3. Brewer, B. W., Van Raalte, J. L., & Linder, D. E. (1993). Athletic identity: Hercules' muscles or Achilles' heel? International Journal of Sport Psychology, 24(2), 237–254.
  4. Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guilford Press.
  5. Coyne, J. O. C., Coutts, A. J., Newton, R. U., & Haff, G. G. (2022). The current state of subjective training load monitoring: Follow-up and future directions. Sports Medicine–Open, 8, Article 53. https://doi.org/10.1186/s40798-022-00433-y
  6. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
  7. Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  8. Feltz, D. L., Short, S. E., & Sullivan, P. J. (2008). Self-efficacy in sport. Human Kinetics.
  9. Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. https://doi.org/10.1037/1082-989X.9.4.466
  10. Fox, K. R., & Corbin, C. B. (1989). The Physical Self-Perception Profile: Development and preliminary validation. Journal of Sport and Exercise Psychology, 11(4), 408–430. https://doi.org/10.1123/jsep.11.4.408
  11. Jekauc, D., Fiedler, J., Wunsch, K., Mülberger, L., Burkart, D., Kilgus, A., & Fritsch, J. (2025). The effect of self-confidence on performance in sports: A meta-analysis and narrative review. International Review of Sport and Exercise Psychology, 18(1), 345–371. https://doi.org/10.1080/1750984X.2023.2222376
  12. Kane, M. T. (2013). Validating the interpretations and uses of test scores. Journal of Educational Measurement, 50(1), 1–73. https://doi.org/10.1111/jedm.12000
  13. Kellmann, M., Bertollo, M., Bosquet, L., Brink, M., Coutts, A. J., Duffield, R., Erlacher, D., Halson, S. L., Hecksteden, A., Heidari, J., Kallus, K. W., Meeusen, R., Mujika, I., Robazza, C., Skorski, S., Venter, R., & Beckmann, J. (2018). Recovery and performance in sport: Consensus statement. International Journal of Sports Physiology and Performance, 13(2), 240–245. https://doi.org/10.1123/ijspp.2017-0759
  14. Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
  15. Levene, H. (1960). Robust tests for equality of variances. In I. Olkin (Ed.), Contributions to probability and statistics (pp. 278–292). Stanford University Press.
  16. Lochbaum, M., Sisneros, C., Cooper, S., & Terry, P. C. (2023). Pre-event self-efficacy and sports performance: A systematic review with meta-analysis. Sports, 11(11), Article 222. https://doi.org/10.3390/sports11110222
  17. Lochbaum, M., Stoner, E., Hefner, T., Cooper, S., Lane, A. M., & Terry, P. C. (2022). Sport psychology and performance meta-analyses: A systematic review of the literature. PLOS ONE, 17(2), e0263408. https://doi.org/10.1371/journal.pone.0263408
  18. Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/biomet/57.3.519
  19. Marsh, H. W., & Redmayne, R. S. (1994). A multidimensional physical self-concept and its relation to multiple components of physical fitness. Journal of Sport and Exercise Psychology, 16(1), 43–55. https://doi.org/10.1123/jsep.16.1.43
  20. McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum Associates.
  21. Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50(9), 741–749. https://doi.org/10.1037/0003-066X.50.9.741
  22. Neupert, E. C., Gupta, L., Holder, T., & Jobson, S. A. (2022). Athlete monitoring practices in elite sport in the United Kingdom. Journal of Sports Sciences, 40(13), 1450–1457. https://doi.org/10.1080/02640414.2022.2085435
  23. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  24. Rebelo, A., Bishop, C., Thorpe, R. T., Turner, A. N., & Gabbett, T. J. (2026). Monitoring training effects in athletes: A multidimensional framework for decision-making. Sports Medicine, 56, 1603–1624. https://doi.org/10.1007/s40279-026-02417-4
  25. Sansone, P., Rago, V., Kellmann, M., & Alcaraz, P. E. (2023). Relationship between athlete-reported outcome measures and subsequent match performance in team sports: A systematic review. Journal of Strength and Conditioning Research, 37(11), 2302–2313. https://doi.org/10.1519/JSC.0000000000004605
  26. Setia, M. S. (2016). Methodology series module 3: Cross-sectional studies. Indian Journal of Dermatology, 61(3), 261–264. https://doi.org/10.4103/0019-5154.182410
  27. Süleymanoğulları, M. (2025). Perceived performance in sports scale: Validity and reliability study. International Journal of Health, Exercise, and Sport Sciences, 2(3), 79–92. https://doi.org/10.5281/zenodo.17426423
  28. Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson.
  29. Tukey, J. W. (1949). Comparing individual means in the analysis of variance. Biometrics, 5(2), 99–114. https://doi.org/10.2307/3001913
  30. Weinberg, R. S., & Gould, D. (2023). Foundations of sport and exercise psychology (8th ed.). Human Kinetics.