Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method

[{“box”:0,”content”:”n[if 992 equals=”Open Access”]n

n

n

n

Open Access

nn

n

n[/if 992]n[if 2704 equals=”Yes”]n

n

Notice

nThis is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.n

n[/if 2704]n

n

Year : 2025 [if 2224 equals=””]14/09/2025 at 4:53 PM[/if 2224] | [if 1553 equals=””] Volume : 02 [else] Volume : [/if 1553] | [if 424 equals=”Regular Issue”]Issue : [/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02 | Page :

n

n

nn

n

n

n

    By

    n

    [foreach 286]n

    n

    Arjun Prakash Mane, Jaydip Yuvaraj Patil,

    n t

  • n

    n[/foreach]

    n

n[if 2099 not_equal=”Yes”]n

    [foreach 286] [if 1175 not_equal=””]n t

  1. Biostatistician, Assistant Professor, Manav Rachna International Institute of Research and Studies, Faridabad, SNBP College of Arts, Commerce, Science and Management of Studies, Pune, Haryana, Maharashtra, India, India
  2. n[/if 1175][/foreach]

n[/if 2099][if 2099 equals=”Yes”][/if 2099]n

n

Abstract

n

n

nThis study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. We analyzed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various indicators. PCA ranked players according to their participation level, with the first three principal components accounting for nearly 90% of the data’s variability. Our analysis reveals Sachin Tendulkar and Muthaiya Muralidharan as top-ranked batsmen and bowlers, respectively. This study provides a comprehensive evaluation of cricket player performance, highlighting the effectiveness of PCA and weighted average approaches. The findings demonstrate the applicability of this methodology in selecting the best cricket squad and offer insights into the strengths and weaknesses of top players. This research contributes to sports analytics, providing a robust framework for evaluating cricket player performance and informing decision-making in team selection and strategy development.nn

n

n

n

Keywords: PCA, Weighted Average Method, Heat Map, Scree Plot, Ranking

n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Sports ]

n

[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Recent Trends in Sports (rts)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

n

n

n

How to cite this article:
nArjun Prakash Mane, Jaydip Yuvaraj Patil. [if 2584 equals=”][226 wpautop=0 striphtml=1][else]Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method[/if 2584]. Recent Trends in Sports. 13/09/2025; 02(02):-.

n

How to cite this URL:
nArjun Prakash Mane, Jaydip Yuvaraj Patil. [if 2584 equals=”][226 striphtml=1][else]Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method[/if 2584]. Recent Trends in Sports. 13/09/2025; 02(02):-. Available from: https://journals.stmjournals.com/rts/article=13/09/2025/view=0

nn

n

n[if 992 equals=”Open Access”]Full Text PDF[/if 992]n

n

n[if 992 not_equal=”Open Access”]n

n

n[/if 992]n

nn

n nn

n[if 379 not_equal=””]nn

Browse Figures

n

n

n[foreach 379]

figures

[/foreach]n

n

n

n[/if 379]

n

n

n

n

n

References n

n[if 1104 equals=””]n

1. Yin W, Ye Z, Shah WUH. Indices Development for Player’s Performance Evaluation through the Super-SBM Approach in Each Department for All Three Formats of Cricket. Sustainability. 2023; 15(4):3201. https://doi.org/10.3390/su15043201
2. Kapil Gupta, an integrated batting performance analytics model for women’s cricket using Principal Component Analysis and Gini scores, Decision Analytics Journal, Volume 4, 2022, 100109, ISSN 2772-6622, https://doi.org/10.1016/j.dajour.2022.100109.
3. Mohammad Reza Mahmoudi, Mohammad Hossein Heydari, Sultan Noman Qasem, Amirhosein Mosavi, Shahab S. Band, Principal component analysis to study the relations between the spread rates of COVID-19 in high risks countries, Alexandria Engineering Journal, Volume 60, Issue 1, 2021, Pages 457-464, ISSN 1110-0168, https://doi.org/10.1016/j.aej.2020.09.013.
4. Shah, Parag & Patel, M. (2018). Ranking the cricket captains using principal component analysis. 10.13140/RG.2.2.33455.38564.
5. Manage, Ananda & Scariano, Stephen. (2013). An Introductory Application of Principal Components to Cricket Data. Journal of Statistics Education. 21. 10.1080/10691898.2013.11889689.
6. Zhang Z, Castelló A. Principal components analysis in clinical studies. Ann Transl Med. 2017 Sep;5(17):351. doi: 10.21037/atm.2017.07.12. PMID: 28936445; PMCID: PMC5599285.
7. Das, Nayan & Mukherjee, Imon & Paul, Goutam & Priya, Ratna. (2023). A Multiple Criteria Decision Making Approach for Ranking Cricket Captains. 10.1109/GCON58516.2023.10183420.
8. Jadwani, Yash & Denholm-Price, James & Hunter, Gordon. (2023). A Machine Learning-based Approach to Analyse Player Performance in T20 Cricket Internationals.
9. Yenuga, B. R. (2022). Selection of Best Players in ODI Cricket using Ranking Based Indexing Method (Doctoral dissertation, Dublin, National College of Ireland).
10. Gløersen Ø, Myklebust H, Hallén J, Federolf P. Technique analysis in elite athletes using principal component analysis. J Sports Sci. 2018 Jan;36(2):229-237. doi: 10.1080/02640414.2017.1298826. Epub 2017 Mar 13. PMID: 28287028.
11. León-Mantero C, Casas-Rosal JC, Pedrosa-Jesús C, Maz-Machado A (2020) Measuring attitude towards mathematics using Likert scale surveys: The weighted average. PLoS ONE 15(10): e0239626. https://doi.org/10.1371/journal.pone.0239626
12. Pessanha Santos N. The Expansion of Data Science: Dataset Standardization. Standards. 2023; 3(4):400-410. https://doi.org/10.3390/standards3040028
13. Hitesh Mangtani (2021); Futuristic accession of Test Cricket: A Statistical Tour; International Journal of Scientific and Research Publications (IJSRP) 11(2) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.11.02.2021.p11004
14. Holubova, Halyna. (2023). A comparative analysis of the principal component method and parallel analysis in working with official statistical data. Statistics in Transition new series. 24. 199-212. 10.59170/stattrans-2023-011.
15. Manage, Ananda & Kafle, Ram & Wijekularathna, Danush. (2020). Classification of all-rounders in limited over cricket – a machine learning approach. Journal of Sports Analytics. 6. 1-12. 10.3233/JSA-200467.
16. Khan, Sheharyar & Ishtiaq, Muhammad & Bibi, Kainat & Amin, Rashid & Ahmed, Adeel & Chaudhary, Iqra. (2021). Statistical Analysis of Cricket Leagues Using Principal Component Analysis. Journal of Engineering and Applied Sciences. Vol 2 No 1 (2021). 30-40. 10.33897/fujeas.v2i1.451.
17. Hussain, Akbar & Qiang, Yan & Ullah, Inam & Ullah, Najeeb & Qudoos, Abdul. (2019). Region-based Teams Ranking in the Game of Cricket using PageRank Algorithm. International Journal of Computer Applications. 177. 10-15. 10.5120/ijca2019919458.
18. Patil, R., Duraphe, A., Motarwar, P., Suganya, G., Premalatha, M. (2023). Cluster-Centric Based Hybrid Approach for Cricket Sports Analytics Using Machine Learning. In: Kottursamy, K., Bashir, A.K., Kose, U., Uthra, A. (eds) Deep Sciences for Computing and
19. Communications. IconDeepCom 2022. Communications in Computer and Information Science, vol 1719. Springer, Cham. https://doi.org/10.1007/978-3-031-27622-4_21
20. Souza, A.S., Bezerra, M.A., Cerqueira, U.M.F.M. et al. An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples. Food Sci Biotechnol 33, 1323–1336 (2024). https://doi.org/10.1007/s10068-023-01509-5
21. Akhtar, S., Scarf, P. & Rasool, Z. Rating players in test match cricket. J Oper Res Soc 66, 684–695 (2015). https://doi.org/10.1057/jors.2014.30
22. Bharadwaj, F., Saxena, A., Kumar, R., Kumar, R., Kumar, S., Stević, Ž. (2024). Player performance predictive analysis in cricket using machine learning. Revue d’Intelligence Artificielle, Vol. 38, No. 2, pp. 449-457. https://doi.org/10.18280/ria.380208

nn[/if 1104][if 1104 not_equal=””]n

    [foreach 1102]n t

  1. [if 1106 equals=””], [/if 1106][if 1106 not_equal=””],[/if 1106]
  2. n[/foreach]

n[/if 1104]

n


nn[if 1114 equals=”Yes”]n

n[/if 1114]

n

n

[if 424 not_equal=””][else]Ahead of Print[/if 424] Subscription Original Research

n

n

n

n

n

Recent Trends in Sports

n

[if 344 not_equal=””]ISSN: [/if 344]

n

n

n

nn

n

[if 2146 equals=”Yes”][/if 2146][if 2146 not_equal=”Yes”][/if 2146]n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n

n[if 1748 not_equal=””]

[else]

[/if 1748]n

n[if 1746 equals=”Retracted”]n

n

n

n

[/if 1746]n[if 4734 not_equal=””]

n

n

n

[/if 4734]n

n

Volume 02
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received 11/06/2025
Accepted 10/09/2025
Published 13/09/2025
Retracted
Publication Time 94 Days

n

n

nn


n

Login

n
My IP
n

PlumX Metrics

nn

n

n

n[if 1746 equals=”Retracted”]n

[/if 1746]nnn

nnn”}]