Futsal Match-Related Fatigue Affects Running Performance and Neuromuscular Parameters but Not Finishing Kick Speed or Accuracy

Abstract

Purpose: The aim of the present study was to investigate the influence of futsal match-related fatigue on running performance, neuromuscular variables, and finishing kick speed and accuracy.Methods: Ten professional futsal players participated in the study (age: 22.2 ± 2.5 years) and initially performed an incremental protocol to determine maximum oxygen uptake (trueV˙O2max: 50.6 ± 4.9 mL.kg−1.min−1). Next, simulated games were performed, in four periods of 10 min during which heart rate and blood lactate concentration were monitored. The entire games were video recorded for subsequent automatic tracking. Before and immediately after the simulated game, neuromuscular function was measured by maximal isometric force of knee extension, voluntary activation using twitch interpolation technique, and electromyographic activity. Before, at half time, and immediately after the simulated game, the athletes also performed a set of finishing kicks for ball speed and accuracy measurements.Results: Total distance covered (1st half: 1986.6 ± 74.4 m; 2nd half: 1856.0 ± 129.7 m, P = 0.00) and distance covered per minute (1st half: 103.2 ± 4.4 m.min−1; 2nd half: 96.4 ± 7.5 m.min−1, P = 0.00) demonstrated significant declines during the simulated game, as well as maximal isometric force of knee extension (Before: 840.2 ± 66.2 N; After: 751.6 ± 114.3 N, P = 0.04) and voluntary activation (Before: 85.9 ± 7.5%; After: 74.1 ± 12.3%, P = 0.04), however ball speed and accuracy during the finishing kicks were not significantly affected.Conclusion: Therefore, we conclude that despite the decline in running performance and neuromuscular variables presenting an important manifestation of central fatigue, this condition apparently does not affect the speed and accuracy of finishing kicks.

Game Running Performance and Fitness in Women’s Futsal

“…Environmental temperature and relative humidity were around 32 °C and 65 %, respectively. Running data was computed for all players across the game duration using DVIDEOW automatic tracking interface, with average error of 0.14-0.19 m and 0.81-0.93 % to determine static position and distances covered on the court, respectively [26,39].…”

“…After frame marking, data matrices containing spatial information of the players as a function of the time (x(t), y(t)) were obtained using the 2D Direct Linear Transformation (DLT) reconstruction method embedded in the software. These were then exported to treatment in Matlab ® R2011b environment (The MathWorks Inc., USA), being smoothed using a third-order low-pass Butterworth digital filter, adopting a cut-off frequency of 0.4 Hz, determined according to previous studies [3,4,26,39].…”

“…Despite the findings that traditional distance-based metrics used to define running performance seem less stable than additional data from inertial micro sensors [23] and that contextual factors (e. g. score status, opposition quality and game location) might also have influenced results [9,24], existing preliminary evidence would suggest that outcomes from fitness tests are not linked to game performance in futsal. Yet to the extent of our knowledge, no previous scientific studies evaluated game running performance-fitness relationships in female futsal players, besides previous work investigated this question in male futsal [5,25,26], soccer [27][28][29][30][31] and in woman solely in the soccer context [32,33].…”

Efeitos do treinamento pliométrico em variáveis fisiológicas e neuromusculares de corredores de longa distância

“…Este procedimento foi realizado de acordo com Milioni et al (2016), de forma que um fio de aço inextensível foi acoplado a uma cinta de velcro presa acima do maléolo lateral da perna dominante, transpassando uma roldana com resistência desprezível e conectando-se a uma célula de carga (CSR-200kg, MK Controle®, São Paulo, Brasil) com frequência de aquisição de 1000 Hz, posicionada na parte posterior do assento da cadeira. O sinal da célula de carga foi adquirido por meio de uma placa de aquisição de sinais analógico-digitais (NI-USB 6009, National Instruments®, Austin, Texas, USA) e suavizado em filtro butterworth com 15 Hz de frequência de corte com auxílio de rotinas especificamente criadas para estes dados no software Matlab® (The Math Works Inc, Natick, Massachussets, USA).…”

“…Por meio da análise do sinal adquirido da célula de carga, foram possíveis as determinações dos valores de força pico de contração isométrica absoluta e relativa à massa corporal, tempo da força pico (tempo decorrido do início da contração até o ponto mais elevado na curva de força) e taxa de desenvolvimento de força (razão entre o valor absoluto da força pico e o tempo até atingi-la). Durante a execução de cada CIVM, os participantes eram verbalmente incentivados a atingir a força máxima no menor intervalo de tempo possível e sustentá-la durante toda a tarefa (MILIONI et al, 2016). Em alguns casos os sujeitos interromperam o teste antes de completarem o tempo total do estágio final, sendo necessária a realização de um cálculo para encontrar a VPE (devido ao valor inteiro ser assumido somente quando o estágio final é completado), em adaptação ao cálculo proposto por Kuipers et al, (1985) e também descrito por Kuipers et al, (2003) Figura 3.…”