selection – The Sport Journal

Testing the predictive validity of combine tests among junior elite football players: an 8-yr follow-up

Authors: Pierre-Luc Yao¹, Vincent Huard Pelletier¹, and Jean Lemoyne¹

¹ Department of Human Kinetics, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada

Corresponding Author:
Pierre-Luc Yao, PhD
3351 Boulevard des Forges
Trois-Rivières, QC, Canada, G8Z 4M3
Pierre-Luc.Yao@uqtr.ca
819 376-5011, ext. 3793

Pierre-Luc Yao, PhD a lecturer and internship coordinator in the Department of Human Kinetics at Université du Québec à Trois-Rivières in Trois-Rivières, Québec. His research interests include psychometrics, sport retirement impacts and athlete development.

Vincent Huard Pelletier, MSc, PhD(c) is currently a doctoral student at Université du Québec à Trois-Rivières. Vincent research interest include athlete development, physical activity behavior amongst athletes.

Jean Lemoyne is professor of physical education in the Department of Human Kinetics at the Université du Québec à Trois-Rivières. His research interests are practice of sport amongst teens and young adults, performance evaluation in sports, advanced statistics in sports.

Testing the predictive validity of combine tests among junior elite football players: an 8-yr follow-up

ABSTRACT

Purpose: The objective of this study was to assess the relationship and contribution of physical performance test results on the final selection of an elite under-18 football selection camp. Methods: Data were drawn from 2 876 players divided into seven position groups (DB, DL, OL, LB, QB, RB, and WR) collected over an 8-year span. Players’ evaluations included performance tests (10-yd dash, 20-yd dash, 40-yd dash, 20-yd pro agility shuttle, 3-cone drill, broad jump, vertical jump, power max test) and anthropometric measures (height and weight). Student t tests were calculated for selected and non-selected groups for all positions. Results: Mean comparisons showed that for most measures, selected players obtained significantly better results than non-selected players. Linear regression models were generated for all groups, and every position was found to have its own unique prediction model. The best models were those of the DL (R² = 0.222), OL (R² = 0.207) and LB (R² = 0.204), and the overall explained variance for each model was considered low (R² = 0.173). Weight, height and 40-yd dash were the most predominant factors in all models. Conclusion: Individually, selection camp results effectively discriminate between selected and non-selected players; together, however, they explain only a limited part of the final selection for each position. Applications in sport: These results suggest that the predictive capacity of the football combine could be improved in terms of the selection of elite football players.

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Sample Distribution and Research Design Are Methodological Dilemmas When Identifying Selection and Using Relative Age as an Explanation of Results

Authors: Torsten Buhre and Oscar Tschernij

Corresponding Author:
Torsten Buhre, PhD
Department of Sport Sciences
Malmö University
20506 Malmö
Sweden
+46-40-665845
torsten.buhre@mah.se

Torsten Buhre is the senior physiologist at the Department of Sport Sciences at Malmö University

Sample distribution and research design are methodological dilemmas when identifying selection and using relative age as an explanation of results

ABSTRACT
The use of a statistical test, such as the chi-squared test, to determine if selection has occurred within a sport has been used frequently in research. The assumed distribution of a sample could influence the occurrence of significant outcomes. The occurrence of significance is generally interpreted as RAE and explained as a result of selection within the sport. Most studies in this field have been done using a cross-sectional design. Therefore, the purpose of this study was to examine the influence of using different types of distribution when testing for significance, in swimming as an example, over a nine-year period of six cohorts in age by gender groups.

Results show that using either an assumed uniformed distribution or a proportional distribution of the national population distribution will lead to an increased number of significant results, in comparison to using either a distribution of the actual sample of the specific age by gender group or the distribution of the previous year within the age by gender group. In addition, when using a longitudinal design over a nine-year period, the occurrence of significance decreased over time. In order to interpret significant results as a consequence of selection within a sport the use of a sport specific and age by gender distribution and a longitudinal design is proposed.
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