{'fraction_non_alphanumeric': 0.03718728870858688, 'fraction_numerical': 0.03380662609871535, 'mean_word_length': 5.090534979423868, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Mathematical models to identify high-performance players for the Brazilian under-19 men’s volleyball team

ABSTRACT The objective of this study was to identify parameters that best discriminate between selected and non-selected players for the Brazilian under-19 men’s volleyball team and propose mathematical models to identify high-performance players. To this end, 18 selected (16.89±0.96 years) and 138 non-selected (16.91±0.74 years) players for the under-19 team were assessed for the training profile, anthropometric profile, and physical performance level. The discriminant function analysis was used to build the models, with a significance of α<0.05. The spike jump reach showed a greater correlation with the discriminant scores obtained in the two models (r=0.701; r=0.782). The 10 variables included in Model 1 helped identify 88.9% of the players selected in their group of origin; Model 2 – obtained by the spike jump reach and duration of playing experience – identified 83.3% of the players selected. Therefore, coaches should be aware that differences between the selected and non-selected players are multi-factorial, with the spike jump reach being the most relevant assessment factor. Furthermore, good players for the selection can be identified using the two models: Model 1 promises greater success with ten assessments, whereas Model 2 allows the identification of suitable players for the under-19 men’s volleyball team with only two simple assessments.