Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

<b>FOOTBALL PERFORMANCE ANALYSIS IN AFRICA</b>

Type de record:

paper
Créateur:
Chi
Éditeur:
fig
Hôte:avatar
Performance Analysis (PA) has revolutionized football by enhancing tactical decision-making through data-driven insights. This study explores PA adoption in African football, focusing on software usage, data perception, and associated challenges. A mixed-method approach was employed, combining survey responses (n=37) and qualitative interviews (n=5) to assess PA integration.Findings indicate a growing awareness of performance analysis, yet financial constraints, lack of training programs, and resistance from coaching staff hinder its widespread adoption. While analysts utilize tools like Nacsport, access to performance data remains limited. South Africa leads in performance analysis implementation in African football; however, other regions struggle with infrastructural barriers. The study also highlights a lack of standardized PA training programs, leading to inconsistencies in data interpretation and application. To bridge the gap, increased investment in training, technology, and institutional support is recommended.This study contributes to understanding performance analysis’s role in African football and proposes solutions for its sustainable growth.

Visit

doi.orgfigshare.com

Tags

Sports science and exercise not elsewhere classifiedAfrican literature

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similaires

<b>High performance of Random Forest algorithm in discriminating the alien species</b><b> </b><b><i>Equisetum hyemale</i></b><b>L. from native and morphologically similar species in South Africa</b><b>National scale-up of etiological testing for </b><b><i>N. gonorrhoeae</i></b><b> and </b><b><i>C. trachomatis</i></b><b> in South Africa: a health economic modelling analysis</b><b>ASSESSMENT OF GLOBAL HYDROLOGICAL MODEL PERFORMANCE AGAINST OBSERVED DISCHARGE DATA</b><b><i>Application to Africa River Basins</i></b><b>A Step</b>‑<b>by</b>‑<b>Step Excel Workbook Template for Reflexive Thematic Analysis</b><b>Mental Health and Wellbeing</b><b>: A Practical- Theological Investigation of </b><b>the </b><b>Impact of</b><b> </b><b>Traditional Healing</b><b> Processes on </b><b>Mental Health Patients</b><b> </b><b>in the Nongoma District of KZN, South Africa</b><b><i>.</i></b><b>How does FinTech affect growth, poverty, and inequality?</b><b> A </b><b>dynamic panel threshold analysis </b><b>for African countries</b>

<b>High performance of Random Forest algorithm in discriminating the alien species</b><b> </b><b><i>Equisetum hyemale</i></b><b>L. from native and morphologically similar species in South Africa</b>

This dataset includes:

  1. hyperspectral data for Equisetum hyemale, E

<b>National scale-up of etiological testing for </b><b><i>N. gonorrhoeae</i></b><b> and </b><b><i>C. trachomatis</i></b><b> in South Africa: a health economic modelling analysis</b>

Models for symptomatic and asymptomatic STI testing for Neisseria gonorrhea and Chlamydia trachomati

<b>ASSESSMENT OF GLOBAL HYDROLOGICAL MODEL PERFORMANCE AGAINST OBSERVED DISCHARGE DATA</b><b><i>Application to Africa River Basins</i></b>

Reliable river discharge information is essential for flood forecasting, drought monito

<b>A Step</b>‑<b>by</b>‑<b>Step Excel Workbook Template for Reflexive Thematic Analysis</b>

A Microsoft Excel template, Thematic Analysis Roadmap, to be utilized when conducting a

<b>Mental Health and Wellbeing</b><b>: A Practical- Theological Investigation of </b><b>the </b><b>Impact of</b><b> </b><b>Traditional Healing</b><b> Processes on </b><b>Mental Health Patients</b><b> </b><b>in the Nongoma District of KZN, South Africa</b><b><i>.</i></b>

Indigenous healing is a practice that cuts across through the entire history of the African continen

<b>How does FinTech affect growth, poverty, and inequality?</b><b> A </b><b>dynamic panel threshold analysis </b><b>for African countries</b>

The dataset is used to examine the nonlinear and threshold effects of FinTech on growth, inequality