@article{10.11648/j.sjams.20261402.11,
  author = {Innocent Chukwudozie Nwokike and Chrysogonus Chinagorom Nwaigwe and Godwin Onyeka Nwafor and Jessica Onyinyechi Obioma and Collins Onyedikachi Ukachukwu and Obi Martins Chuks},
  title = {Analysis of the Attributes of a Left-Right Football Midfielder},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {14},
  number = {2},
  pages = {49-57},
  doi = {10.11648/j.sjams.20261402.11},
  url = {https://doi.org/10.11648/j.sjams.20261402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20261402.11},
  abstract = {The availability of player performance data has significantly enhanced the scope and depth of quantitative analysis in recent professional football; however, position-specific statistical investigations, especially for specialized roles such as wide midfielders, remain relatively unavailable. This study addresses this gap by carefully studying these correlations and picking out relevant determinants of players' performance for left and right midfield positions using adequate multivariate statistical techniques. A comprehensive dataset comprising physical, technical, and mental attributes of modern-day professional players occupying these wide midfield positions was collected and subjected to rigorous statistical procedures. The study also deployed Pearson correlation analysis to explore linear relationships between individual player attributes and overall performance ratings. Canonical correlation analysis (CCA) was used to determine the relative contribution of each attribute, as well as principal component analysis (PCA), to uncover latent performance dimensions and reduce redundancy among some of the highly correlated variables. The empirical results show that physical and mental attributes, especially ball control, dribbling, vision, short passing, and composure, show strong positive correlations with the general performance ratings of the players. In contrast, physical attributes such as sprint speed and acceleration show comparatively weaker and less consistent relationships. Furthermore, the presence of strong intercorrelations among technical variables suggests substantial overlap among performance indicators, therefore, justifying the use of dimensionality-reduction techniques in the study. Finally, the study highlights the importance of technical proficiency and decision-making ability in determining the effectiveness of wide midfielders. These revelations provide valuable empirical support for data-driven approaches to identification of talent, player development, tactical improvements and maximization, and scouting strategies in modern football analytics.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Analysis of the Attributes of a Left-Right Football Midfielder
AU  - Innocent Chukwudozie Nwokike
AU  - Chrysogonus Chinagorom Nwaigwe
AU  - Godwin Onyeka Nwafor
AU  - Jessica Onyinyechi Obioma
AU  - Collins Onyedikachi Ukachukwu
AU  - Obi Martins Chuks
Y1  - 2026/05/29
PY  - 2026
N1  - https://doi.org/10.11648/j.sjams.20261402.11
DO  - 10.11648/j.sjams.20261402.11
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 49
EP  - 57
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20261402.11
AB  - The availability of player performance data has significantly enhanced the scope and depth of quantitative analysis in recent professional football; however, position-specific statistical investigations, especially for specialized roles such as wide midfielders, remain relatively unavailable. This study addresses this gap by carefully studying these correlations and picking out relevant determinants of players' performance for left and right midfield positions using adequate multivariate statistical techniques. A comprehensive dataset comprising physical, technical, and mental attributes of modern-day professional players occupying these wide midfield positions was collected and subjected to rigorous statistical procedures. The study also deployed Pearson correlation analysis to explore linear relationships between individual player attributes and overall performance ratings. Canonical correlation analysis (CCA) was used to determine the relative contribution of each attribute, as well as principal component analysis (PCA), to uncover latent performance dimensions and reduce redundancy among some of the highly correlated variables. The empirical results show that physical and mental attributes, especially ball control, dribbling, vision, short passing, and composure, show strong positive correlations with the general performance ratings of the players. In contrast, physical attributes such as sprint speed and acceleration show comparatively weaker and less consistent relationships. Furthermore, the presence of strong intercorrelations among technical variables suggests substantial overlap among performance indicators, therefore, justifying the use of dimensionality-reduction techniques in the study. Finally, the study highlights the importance of technical proficiency and decision-making ability in determining the effectiveness of wide midfielders. These revelations provide valuable empirical support for data-driven approaches to identification of talent, player development, tactical improvements and maximization, and scouting strategies in modern football analytics.
VL  - 14
IS  - 2
ER  - 

Copy | Download