A Multidisciplinary Investigation into the Talent Development Processes at an English Football Academy: A Machine Learning Approach
Abstract
:1. Introduction
2. Exploring the Developmental Characteristics of under-9 to under-16 Football Academy Players
2.1. Methods
2.1.1. Sample
2.1.2. Measures and Procedures
Four Football-Specific Technical Tests
Eight Match Analysis Statistics from across the Entire Season
Three Perceptual-Cognitive Expertise Video Simulation Tests
Eight Anthropometric Measures
Eight Fitness Tests
Six Factors from the 59-Item Psychological Characteristics for Developing Excellence Questionnaire
Ten Items from the Participation History Questionnaire
Six Measures from Postcode Data
2.1.3. Player Review Ratings
2.1.4. Data Analysis
2.2. Results
2.3. Discussion
3. The Junior-to-Senior Transition from Youth Academy to Professional Level: Exploring the Characteristics of Selected and Deselected under-18 Players
3.1. Methods
3.1.1. Sample
3.1.2. Measures and Procedures
3.1.3. Data Analysis
3.2. Results
3.3. Discussion
4. Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Feature | Coefficient/SD of Feature |
---|---|
Ball juggling | 0.083 |
Lob pass | 0.160 |
Average dribble competition percentage | 0.124 |
PCE ‘at’ | 0.091 |
PCE ‘post’ | 0.062 |
PCDEQ Factor 3 | 0.062 |
Total match-play hours | 0.145 |
Total individual practice hours | −0.027 |
0–30 m sprint | −0.041 |
CMJ height | 0.053 |
Percentage of predicted adult height attained | 0.196 |
Birth quarter 2 (reduced relative to birth quarter 1) | −0.133 |
Birth quarter 4 (reduced relative to birth quarter 1) | −0.060 |
Home postcode social grade 2 (reduced in comparison to social grade 1 or 4) | −0.082 |
School postcode social grade 3 (reduced relative to social grade 1 or 4) | −0.045 |
Feature | Coefficient/SD of Feature | Odds Ratio/SD of Feature |
---|---|---|
43 progression steps rating | 0.64 | 1.89 |
Slalom dribble | 0.01 | 1.01 |
PCDEQ Factor 3 | 0.44 | 1.55 |
Home postcode social grade 2 | −0.12 | 0.89 |
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Kelly, A.L.; Williams, C.A.; Cook, R.; Sáiz, S.L.J.; Wilson, M.R. A Multidisciplinary Investigation into the Talent Development Processes at an English Football Academy: A Machine Learning Approach. Sports 2022, 10, 159. https://doi.org/10.3390/sports10100159
Kelly AL, Williams CA, Cook R, Sáiz SLJ, Wilson MR. A Multidisciplinary Investigation into the Talent Development Processes at an English Football Academy: A Machine Learning Approach. Sports. 2022; 10(10):159. https://doi.org/10.3390/sports10100159
Chicago/Turabian StyleKelly, Adam L., Craig A. Williams, Rob Cook, Sergio Lorenzo Jiménez Sáiz, and Mark R. Wilson. 2022. "A Multidisciplinary Investigation into the Talent Development Processes at an English Football Academy: A Machine Learning Approach" Sports 10, no. 10: 159. https://doi.org/10.3390/sports10100159