The analysis of penalty kick has played an important role in performance analysis. The study aims are to get formal feedback on the relevance of variables for penalty kick analysis, to design and validate an observational system; and to assess experts’ opinion on the optimum video footage in penalty kick analysis. A structured development process was adopted for content validity, reliability and agreement on video usage. All observational variables included in OSPAF showed Aiken’s V values above the cut-off (for 5-scale V> 0.64; for 2-scale = V > 0.75; p < 0.05). Cohen’s Kappa resulted in mean intra- and inter-rater reliability values of 0.90 and 0.86, respectively. It is recommended to combine at least three different viewing angles (V = 0.90; p = 0.006) with standardization of video quality (V = 0.95; p = 0.006). Changing the viewing angles may influence the observer perception (V = 0.86; p = 0.006). The aerial and pitch-level viewing angle behind the penalty taker and pitch-level viewing angle behind the goalkeeper were indicated as most appropriate for observational analysis (V = 0.97; p = 0.01). The OSPAF met all requirements of instrument validation. It may be recommended as basis of future observational systems on penalty kicks.
Purpose. the study analysed the responses from different training load monitoring tools in the elite U-20 soccer category and checked the level of association between these responses. Methods. the participants were 10 elite male soccer players (age, 18.61 ± 0.95 years; height, 176.81 ± 5.03 cm; body mass, 70.32 ± 8.41 kg). the progressive test to exhaustion assessed maximum oxygen consumption and maximum heart rate. the athletes were monitored over 15 training sessions with a heart-rate-based method (Edwards) and mechanical load indicators obtained from GPS devices (15 Hz). Results. Individual training load was calculated with the Foster's session rating of perceived exertion (session-rPE) procedure. A significant correlation was found between session-rPE and Edwards (0.564, p < 0.05). there were no significant correlations between session-rPE and average speed (-0.161), average heart rate of the training session (-0.187), distance over 20 km/h (0.006), or number of accelerations performed in different zones (-0.194,-0.178,-0.171,-0.236). the Edwards method showed significant correlations with the total distance (0.642, p < 0.01), average heart rate (0.333, p < 0.01), and distances covered at 0-20 km/h (0.634, p < 0.01; 0.568, p < 0.01; 0.424, p < 0.01; 0.289, p < 0.01; 0.201, p < 0.015). there were no significant correlations between Edwards and average speed (0.158), distance over 20 km/h (0.014), number of accelerations performed in different zones (-0.194,-0.178,-0.171,-0.236), or number of normalized accelerations (-0.118,-0.038,-0.058,-0.035). Conclusions. the Edwards method and session-rPE are limited load monitoring tools to indicate the reality of training situations (high-intensity action with recovery intervals).
Background: Several factors may affect the development of a player during the sports training process. Reaction time is considered an important aspect of perceptual skills in sports and can potentially affect football performance. During the maturation process of a player there may be changes in the cognitive skills, in addition to changes in the training levels that this player is submitted to. The aim of this study is to compare the discriminative reaction time (DRT) in elite young football players between categories U-15 and U-17. Methods: Participants were 236 elite Brazilian young male football players from categories U-15 (n = 139, Mage = 14.21, SD = 0.66 years) and U-17 (n = 97, Mage = 17.99, SD = 0.48 years). The Reaction Test (S5 version), provided by the Vienna Test System SPORTS® (VTS) was applied. Results: statistically significant difference was found in the DRT (p = .04) between football players of categories U-15 and U-17. U-17 players faster (M = 526 ms, sd = 65.30) when compared to the U-15 players (M = 543 ms, sd = 62.40), however with a small effect size (.13). Conclusion: Elite football players in the U17 category have better DRT values than players in the U15 category. Resumen. Introducción: Varios factores pueden afectar al desarrollo de un jugador durante el proceso de formación deportiva. El tiempo de reacción se considera un aspecto importante de las habilidades perceptivas en el deporte y puede afectar potencialmente al rendimiento futbolístico. Durante el proceso de maduración de un jugador pueden producirse cambios en las habilidades cognitivas, además de cambios en los niveles de entrenamiento a los que se somete este jugador. El objetivo de este estudio es comparar el tiempo de reacción discriminativo en jóvenes futbolistas de élite entre las categorías sub-15 y sub-17. Métodos: Los participantes fueron 236 jóvenes futbolistas brasileños de élite de las categorías Sub-15 (n = 139, Edad media = 14,21, sd = 0,66 años) y Sub-17 (n = 97, Edad media = 17,99, sd = 0,48 años). Se aplicó el Test de Reacción (versión S5), proporcionado por el Vienna Test System SPORTS® (VTS). Resultados: se encontraron diferencias estadísticamente significativas en el DRT (p = .04) entre los futbolistas de las categorías sub-15 y sub-17. Los jugadores sub-17 fueron más rápidos (M = 526 ms, sd = 65,30) en comparación con los jugadores sub-15 (M = 543 ms, sd = 62,40), aunque con un tamaño del efecto pequeño (.13). Conclusión: Los jugadores de fútbol de élite de la categoría sub17 tienen mejores valores de tiempo de reacción discriminativo que los jugadores de la categoría sub15.
Body orientation of football players has proven to be an informative resource related to successful penalty kicks. OpenPose is one of the most popular open-source pose estimation technologies. This study aims: (i) to verify whether OpenPose can detect relevant body orientation angles from video data of penalty kicks in elite football and (ii) to investigate the relationship between these body angles and observable behaviors analyzed via an observational system for penalty kick analysis in football (OSPAF) with the penalty taker and goalkeeper strategy. A total of 34 penalty videos, with standardized viewing angle, from the main European leagues (2017–2020) were analyzed. Relevant body orientation variables were selected for penalty kicks analysis and were extracted from video data through OpenPose technique. The OSPAF, previously validated by experts, was used. The mean confidence score of OpenPose measures was 0.80 ± 0.14. The mean kappa value for repeated measurements of OpenPose was 0.96 ± 0.04. Logistic regressions were performed to investigate the relationship between OpenPose investigated variables (penalty taker: shoulder, hips, and nonkicking foot orientation; goalkeeper: right and left foot, anticipation), observable behaviors (OSPAF variables), and the strategy (penalty taker: goalkeeper dependent or independent; goalkeeper: shooter dependent or independent) in penalty kicks. The selected body orientation angle (goalkeeper anticipation) measured through OpenPose correlated significantly with the goalkeeper strategy. The prediction model of the goalkeeper's strategy had its accuracy increased to 97% when the variable goalkeeper anticipation was included [χ(35)2 = 49.648, p < 0.001]. Lower degrees of goalkeeper anticipation, the goalkeeper tactical action (awaiting), and run up speed (slow) were associated with a kicker-dependent strategy. Regarding the penalty taker, the selected body angles measured through OpenPose did not associate significantly with the shooter strategy. Body orientation analysis by using OpenPose has shown sufficient reliability and provides practical applications for analyzing the strategies adopted by goalkeepers in penalty kicks in elite football.
This study investigated the differences in external and internal load during pre-season training sessions carried out with different SSGs and a friendly match in top-class professional football players. The study was conducted over a full pre-season. Participants were 9 male top-class professional football players (25 ± 5 years; 74 ± 8 kg; 177 ± 8 cm). The following variables were measured: training session duration (min), average heart rate (bpm), total distance (m), distance covered per minute (m/min), the total number of accelerations > 2.5 m/s2, number of accelerations > 2.5 m/s2 per minute, average distance of accelerations (m), the average value of acceleration (m/s2). One-way ANOVA was performed to analyze the variance of all evaluated variables. No differences were found in the average accelerations (m/s2) (0.128) among all the training formats. Moderate differences were found in number of accelerations > 2.5 m/s2 per minute (η2 = 0.396, moderate effect) and average distance of accelerations (η2 = 0.545). Strong differences were found in HR (η2 = 0.788, large effect), total distance (η2 = 0.797, strong effect), distance per minute (η2 = 0.775 strong effect), total number of accelerations > 2.5 m/s2 (η2 = 0.699 strong effect). Significant correlations were found just for the number of accelerations > 2.5 m/s2 and the number of accelerations > 2.5 m/s2 per minute with the 4v4, 8v8 and the FM (r = 0.828–0.890, r2 = 69% – 79%; p < 0.01). External and internal loads differ across different SSGs and a FM during the pre-season training sessions.
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