Improving Talent Identification Using Insights from Selection Psychology: 5-minute pitch

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Abstract

Talent identification involves the prediction of elite sports performance. According to a recent review, insights from selection psychology can help to provide more accurate predictions of future performance (Den Hartigh, Niessen, Frencken, & Meijer, 2018). One approach to potentially improve such predictions is using ‘sample-based’, as opposed to ‘sign-based’ methods. Sign-based methods are defined as tests that measure distinct (e.g., psychological) constructs that are conceptually related to the criterion. Sample-based methods aim to sample criterion behavior. I will present a study in which we compared the predictive validity of samples of soccer performance in small sided games (SSGs), against the validity of endurance, sprint and agility tests. Thirty-four players of the U-19 and U-23 teams of a professional soccer academy participated in 11 (SD = 3) 7-vs-7 games. Players’ performance was assessed based on their contribution to the result of each SSG outcomes, whereas standardized tests were used to assess speed, endurance, and agility. Whole-season performance ratings (0 – 10) by coaches were used as a criterion measure. For the U-19 players, SSG performance (r = .44) was a stronger predictor of the coaches’ performance rating than speed (r = -.08), endurance (r = .34), and agility (r = -.08). Surprisingly enough, all variables correlated negatively with coaches’ rating for the U-23 players, which might be due to other factors confounding the judgment of the coach in this age category. To conclude, our results provide first evidence that sample-based methods (SSGs) may provide stronger indicators of soccer performance than sign-based tests.
Original languageEnglish
Publication statusPublished - 15-Jul-2019
EventFEPSAC 2019: 15th European Congress of Sport & Exercise Psychology - Münster, Germany
Duration: 15-Jul-201919-Jul-2019

Conference

ConferenceFEPSAC 2019
Country/TerritoryGermany
CityMünster
Period15/07/201919/07/2019

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