Goldfit Soccer:用于识别年轻足球运动员天赋的多维模型。

Francisco Zacaron Werneck, Emerson Filipino Coelho, Marcelo de Oliveira Matta, Rodrigo César Pedrosa Silva, António José Barata Figueiredo
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摘要

有研究提供了实证证据,证明测试组合和 "教练之眼 "对人才识别的预后相关性。本研究的目的是:1)比较未来入选球员和未入选球员的客观和主观评估以及足球专项潜力综合指数;2)评估多维模型作为足球人才识别工具的预后有效性。样本由巴西足球人才培养计划中 U13 至 U17 年龄组的 132 名男性球员(14.5 ± 1.4 岁;地区竞技水平)组成。运动员完成了一项多维测试,并由教练对其运动潜力进行了主观评价。五年后对球员的成功进行了评估,评估结果以获得巴西锦标赛 20 岁以下组别或成年职业水平(成功率为 15.9%)为标准。证实了单变量预后的有效性,未来入选球员在 20 米短跑(p = .009)、敏捷性(p = .04)、反身跳(p = .04)、坐位体前屈(p = .001)、Yo-Yo IR1(p = .001)、运球(p p = .007)、压力下的巅峰状态(p = .01)、自信/动机(p = .03)、应对技能(p = .03)、无形资产(p p p
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Goldfit Soccer: A Multidimensional Model for Talent Identification of Young Soccer Players.

Studies have provided empirical evidence on the prognostic relevance of test batteries and the "coach's eye" for talent identification. The aims were 1) to compare objective and subjective assessments as well as a combined soccer-specific potential index between future selected and non-selected players and 2) to evaluate the prognostic validity of a multidimensional model as a tool for talent identification in soccer. The sample was composed by 132 male players (14,5 ± 1,4 years; regional competitive level) from U13 to U17 age groups of a Brazilian soccer talent development program. Athletes completed a multidimensional test battery and were subjectively rated by their coaches for sporting potential. Players' success was evaluated five years later and was operationalized by achieving under-20 category of the Brazilian Championship or adult professional level (success rate, 15.9%). Confirming univariate prognostic validity, future selected outperformed non-selected players regarding 20-m sprint (p = .009), agility (p = .04), countermovement jump (p = .04), sit-and-reach (p = .001), Yo-Yo IR1 (p = .001), dribbling (p < .001), perceived competence (p = .007), peaking under pressure (p = .01), confidence/motivation (p = .03), coping skills (p = .03), intangibles (p < .001) and player potential (p < .001). A combined index (objective tests, athlete's assessments and coach's eye) named Gold Score Soccer (GSS) showed high prognostic validity (p < .001). A binary logistic regression estimated the probability of success (yes/not) with GSS, ambidextrous and predicted age at peak height velocity as predictors. This multidimensional model named GoldFit Soccer showed high prognostic validity (sensitivity = 85.7%; specificity = 83.8%; accuracy = 84.1%; area under the ROC curve = .93 [.87-.98]). Thus, GoldFit Soccer is a valid multidimensional scientific model for talent identification in soccer.

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