Relationships between Strength and Step Frequency with Fatigue Index in Repeated Sprint Ability

velocity pro le (FVP) and repeated-sprint ability (RSA) tests are indicators of physical capacities in most team sport players. The purpose of this study was to examine the stride kinematics during a repeated-sprint ability (RSA) test and to analyze the relationship between Bosco's force velocity pro le (FVP) and RSA performance in elite female eld hockey players. Thirteen elite-female players performed both RSA (six 30 m maximal sprints) and jumping (CMJ weighted and body weight) tests. Sprinting time fatigue indexes during a 30 m RSA test were correlated with step frequency fatigue indexes (r > 0.7;p< 0.01). CMJ50 showed a large relationship with sprint time fatigue indexes. FV50 showed a very large relationship with sprint time fatigue indexes (r > 0.7; p< 0.01 ), and a large relationship with the step frequency fatigue indexes (r > 0.5;p< 0.05). This study highlighted two possible ways to improve fatigue indexes in RSA, with the aim of maximizing the distances covered at high-intensities during the matches: (a) strength training and (b) focusing on step frequency during

with sprint time fatigue indexes (r > 0.7; p< 0.01 ), and a large relationship with the step frequency fatigue indexes (r > 0.5;p< 0.05). This study highlighted two possible ways to improve fatigue indexes in RSA, with the aim of maximizing the distances covered at high-intensities during the matches: (a) strength training and (b) focusing on step frequency during speed training. Keywords: sport performance analysis; training methods; team sports; monitoring and evaluation of training 1. Introduction Most team sports are characterized by an intermittent activity where periods of short high-intensity efforts are interchanged with periods of active and passive recovery [1–8]. The total sprint distance covered by players in these disciplines is an important performance factor, as noted in eld hockey [1], Australian Football [2], and soccer [3]. Therefore, repeated-sprint ability (RSA) tests have largely been used as an important intermittent sport performance index [4,5], and to track the effectiveness of training programs [6]. Moreover, the ability to perform repeated sprint bouts with a short recovery time between them has been reported to be relevant for eld hockey performance and is worth being evaluated and trained [7,8]. From a physiological perspective, RSA is a complex quality that is essential in order to obtain maximal sprint speed and, at the same time, to achieve the oxidative capacity needed for phosphocreatine recovery and hydrogen buffering [9]. Several physical capacities play a determinant role in RSA. For example, lower-limb strength and power provide acceleration and maximal speed during the rst repetitions of multiple sprints [10]. This highlights the important of a well-developed neuromuscular system, which for allows a better activation of the motor units [11]. On the other hand, stride kinematics is also a performance determinant in sprinting ability. Speci cally, it has been demonstrated that a higher step frequency through a shorter support time can optimize 60 m sprints [12], and that training at a faster step cadence may improve running economy in female distance runners [13]. Additionally, a previous study reported changes in stride kinematics during RSA tests performed on a treadmill, with the step frequency decreasing during the ve

has been demonstrated that a higher step frequency through a shorter support time can optimize 60 m sprints [12], and that training at a faster step cadence may improve running economy in female distance runners [13]. Additionally, a previous study reported changes in stride kinematics during RSA tests performed on a treadmill, with the step frequency decreasing during the ve Int. J. Environ. Res. Public Health2022,19, 196.

Int. J. Environ. Res. Public Health2022,19, 196 2 of 11 repetitions of 5 s sprints [14]. This nding has also been described to occur during RSA eld tests [15]. However, there is no further information about the evolution of stride kinematics during RSA eld tests. The strength and power values of athletes are critical indicators of sprinting perfor- mance, which, at the same time, is the base of RSA [16]. One of the best indicators of lower limb neuromuscular fatigue is CMJ performance, which has been related to sprint ability [17,18] and has been employed within the Bosco Index to identify the force velocity characteristics of athletes [19,20]. CMJ performance has been used as a tool to individualize training loads during sprinting sessions, providing information about the mechanical and physiological response of athletes, instead of employing a standard xed number of sprints for all players [21]. In addition, it has been recently reported that CMJ performance is related to speci c actions in intermittent-like sports such as eld hockey [22]. Nevertheless, no information about the role of force velocity pro le (FVP) on RSA performance has been previously examined. Therefore, the aim of this study was to examine the stride kinematics during an RSA test, and to analyze the relationship between Bosco´s FVP and RSA performance in elite female eld hockey players. 2. Materials and Methods Thirteen elite-female field hockey players (age 24.9 5.6 years, body height1.67 0.04 m , and body weight 58.7 3.7 kg) participated in this study. The study was carried out in the ninth week of the 2018/2019 season. The study was approved by the Local University Ethics Committee, and participants were fully informed about the protocol of the study and gave their informed consent according to the Declaration of Helsinki. The team staff was involved in the design and supervision of the study, so the research protocol was part of the regular training routine. All test sessions were conducted at the same time of day and during the physical training part of the session that preceded the eld hockey training. Speci cally, the jumping tests

to the Declaration of Helsinki. The team staff was involved in the design and supervision of the study, so the research protocol was part of the regular training routine. All test sessions were conducted at the same time of day and during the physical training part of the session that preceded the eld hockey training. Speci cally, the jumping tests were performed in Tuesday's session (regular strength ses- sion), whereas the RSA test was performed in Thursday's session (regular speed session), both with their respective warm-ups (Figure).Int. J. Environ. Res. Public Health 2022, 19, 196 2 of 11 during RSA tests performed on a treadmill, with the step frequency decreasing during the five repetitions of 5 s sprints [14]. This finding has also been described to occur during RSA field tests [15]. However, there is no further information about the evolution of stride kinematics during RSA field tests. The strength and power values of athletes are critical indicators of sprinting perfor- mance, which, at the same time, is the base of RSA [16]. One of the best indicators of lower limb neuromuscular fatigue is CMJ performance, which has been related to sprint ability [17,18] and has been employed within the Bosco Index to identify the force−velocity char- acteristics of athletes [19,20]. CMJ performance has been used as a tool to individualize training loads during sprinting sessions, providing information about the mechanical and physiological response of athletes, instead of employing a standard fixed number of sprints for all players [21]. In addition, it has been recently reported that CMJ performance is related to specific actions in intermittent-like sports such as field hockey [22]. Neverthe- less, no information about the role of force−velocity profile (FVP) on RSA performance has been previously examined. Therefore, the aim of this study was to examine the stride kinematics during an RSA test, and to analyze the relationship between Bosco´s FVP and RSA performance in elite female field hockey players. 2. Materials and Methods Thirteen elite-female field hockey players (age 24.9 ± 5.6 years, body height 1.67 ± 0.04 m, and body weight 58.7 ± 3.7 kg)

Therefore, the aim of this study was to examine the stride kinematics during an RSA test, and to analyze the relationship between Bosco´s FVP and RSA performance in elite female field hockey players. 2. Materials and Methods Thirteen elite-female field hockey players (age 24.9 ± 5.6 years, body height 1.67 ± 0.04 m, and body weight 58.7 ± 3.7 kg) participated in this study. The study was carried out in the ninth week of the 2018/2019 season. The study was approved by the Local Uni- versity Ethics Committee, and participants were fully informed about the protocol of the study and gave their informed consent according to the Declaration of Helsinki. The team staff was involved in the design and supervision of the study, so the research protocol was part of the regular training routine. All test sessions were conducted at the same time of day and during the physical training part of the session that preceded the field hockey training. Specifically, the jumping tests were performed in Tuesday’s session (regular strength session), whereas the RSA test was performed in Thursday’s session (regular speed session), both with their respective warm-ups (Figure 1). Figure 1. Jumping and RSA test protocols. Figure 1.Jumping and RSA test protocols.

Int. J. Environ. Res. Public Health2022,19, 196 3 of 11 2.1. RSA Test Before testing, all the participants performed a regular, speci c, and standardized 15 minwarm-up comprising 3 min of jogging and displacements using different movement and orientation patterns, 2 min of dynamic light stretching, 3 min of basic muscular activation, 2 min of plyometrics, 3 min of running drills, and 2 min of short distance accelerations. The RSA protocol consisted of six 30 m maximal sprints interspersed with 30 sof active recovery periods, where players decelerated during 10 m and jogged40 mto position themselves for a new start [23]. The sprint times were measured using electronic photocells (Microgate, Bolzano, Italy), which were adjusted according to the height of the players and were placed at 0, 10, 20, and 30 m. Each sprint was initiated from a standing position with their foot 1 m behind the rst timing gate. One xed video camera, EX-ZR800 (Casio Computer Co., Tokio, Japan), located in a lateral view and operating at 60 Hz (shutter speed: 1/1000, 1920 1080 px), recorded the 30 m, similar to previous studies [24,25]. The step frequency (SF = number of steps/time of the number of steps) and step length (SL = sprintdistance/sprint time/step frequency) were determined using a video analysis of the test. The RSA performance was assessed using ve scores for each variable (sprint time, step frequency, and step length): the best, mean, and worst of the six repetitions, and two fatigue indexes, calculated as a percentage decrement from the best value (Fmean = 100 (mean/best*100); Fworst = 100 (worst/best*100)) [26]. 2.2. Jumping Test Before the test, all the participants performed a regular, speci c, and standardized 10 minwarm-up comprising 2 min of general activation, 2 min of light active stretching, 3 minof basic bodyweight muscular activation (10 repetitions of lunges, squats, hip thrusts, and single leg dead lifts), and 3 min of explosive activation (six repetitions of squat jumps, CMJ, and drop jumps). The CMJ and a CMJ50 (CMJ with external loads equivalent to 50% of the players´bodyweight) tests were performed on a contact platform (Chronojump-

of light active stretching, 3 minof basic bodyweight muscular activation (10 repetitions of lunges, squats, hip thrusts, and single leg dead lifts), and 3 min of explosive activation (six repetitions of squat jumps, CMJ, and drop jumps). The CMJ and a CMJ50 (CMJ with external loads equivalent to 50% of the players´bodyweight) tests were performed on a contact platform (Chronojump- BoscoSystem, Barcelona, Spain). Jumping height was determined based on the ight time using Chronojump software (Chronojump-BoscoSystem, Barcelona, Spain). The best of three attempts was selected for each jump. As the players held down a bar on their shoulders during the CMJ50, they were also instructed to hold down a plastic bar during the CMJ to mimic the jumping execution. Participants were instructed to start from a standing position; perform a rapid exion–extension of the legs with a minimum pause between the eccentric and concentric phase of the muscle contraction; bend their knees to a freely chosen angle; perform a maximal jump keeping their body vertical throughout the jump, avoiding undue lateral and frontal movements; and to land with knees fully extended [27,28]. The FV50 was calculated using Bosco´s Index (FVP50 = CMJ50/CMJ*100) [19,20]. 2.3. Statistical Analysis All of the results are expressed as the mean and standard deviation (SD). A repeated measures analysis of variance was used to compare the sprint times, step frequency, and step length across the number of repetitions (1 to 6) and section (0–10 m, 10–20 m, and 20–30 m. Post hoc tests were used to determine the statistical effects (p< 0.05) between factors using Bonferroni corrections, and were interpreted using effect sizes ( p2) with 0.2, 0.5, and 0.8 threshold values for small, medium, and large effects [29]. Pearson correlation coef cients were used to relate the PFV parameters with the RSA kinematic parameters, with 0.1, 0.3, 0.5, 0.7, and 0.9 being the threshold values that represented small, moderate, large, very large, and nearly perfect correlations, respectively [30]. Statistical analyses were performed using the IBM Statistical Package for Social Sciences Statistics, version 22.0 (IBM Inc., Armonk, NY, USA).

relate the PFV parameters with the RSA kinematic parameters, with 0.1, 0.3, 0.5, 0.7, and 0.9 being the threshold values that represented small, moderate, large, very large, and nearly perfect correlations, respectively [30]. Statistical analyses were performed using the IBM Statistical Package for Social Sciences Statistics, version 22.0 (IBM Inc., Armonk, NY, USA).

Int. J. Environ. Res. Public Health2022,19, 196 4 of 11 3. Results 3.1. Repetitions and Sections Analysis The evolution during the six repetitions of the RSA 30-m sprint test (Figure) showed medium differences between repetitions in sprint time (F3.65= 19.73,p< 0.001, 2 = 0.62) and step frequency (F2.70= 24.40,p< 0.001, 2 = 0.67), and trivial differences in step length (F4.57= 2.88,p= 0.026, 2 = 0.19). Pair-wise comparisons in the sprint time and step frequency revealed multiple statistical differences, whereas, for the step length, differences were only found between the last and the fth repetition (p= 0.03). When comparing the rst and the last repetition (Table), the sprint time increased by 4.1% ( p< 0.001), whereas step frequency decreased by 4.0% (p< 0.001) and the step length remained constant.Int. J. Environ. Res. Public Health 2022, 19, 196 4 of 11 3. Results 3.1. Repetitions and Sections Analysis The evolution during the six repetitions of the RSA 30-m sprint test (Figure 2) showed medium differences between repetitions in sprint time (F3.65 = 19.73, p < 0.001, η2 = 0.62) and step frequency (F2.70 = 24.40, p < 0.001, η2 = 0.67), and trivial differences in step length (F4.57 = 2.88, p = 0.026, η2 = 0.19). Pair-wise comparisons in the sprint time and step fre- quency revealed multiple statistical differences, whereas, for the step length, differences were only found between the last and the fifth repetition (p = 0.03). When comparing the first and the last repetition (Table 1), the sprint time increased by 4.1% (p < 0.001), whereas step frequency decreased by 4.0% (p < 0.001) and the step length remained constant. Figure 2. Evolution of step kinematics during RSA in elite female field hockey players. (*) Different from the first repetition at p < 0.05; (#) different from the last repetition at p < 0.05. Table 1. Percentage changes in relation to the first repetition of the stride kinematics during RSA in elite female field hockey players. (*) Different from the first repetition at p < 0.05. Variables Repetition 2 3 4 5 6 Sprint Time 1.0 ± 0.4% 2.1

repetition at p < 0.05; (#) different from the last repetition at p < 0.05. Table 1. Percentage changes in relation to the first repetition of the stride kinematics during RSA in elite female field hockey players. (*) Different from the first repetition at p < 0.05. Variables Repetition 2 3 4 5 6 Sprint Time 1.0 ± 0.4% 2.1 ± 0.5% * 3.2 ± 0.6% * 3.5 ± 0.8% * 4.1 ± 0.5% * Step Frequency −1.6 ± 0.4% −3.3 ± 0.5% * −3.9 ± 0.7% * −4.4 ± 0.8% * −4.0 ± 0.6% * Step Length 0.6 ± 0.4% 1.3 ± 0.5% 0.9 ± 0.5% 1.1 ± 0.5% 0.1 ± 0.5% The analysis between the sections (0–10 m, 10–20 m, and 20–30 m) showed large dif- ferences in sprint time (F1.39 = 1198.56, p < 0.001, η2 = 0.99) and step length (F2.24 = 1039.43, p < 0.001, η2 = 0.99), and moderate differences in step frequency (F1.5 = 15.65, p < 0.001, η2 = 0.57). Pairwise comparisons (Figure 3) showed differences (p < 0.001) between all the sections for sprint time and step length, while step frequency showed higher values in the 10–20 m section. Figure 2. Evolution of step kinematics during RSA in elite female eld hockey players. (*) Different from the rst repetition atp< 0.05; (#) different from the last repetition atp< 0.05. Table 1. Percentage changes in relation to the rst repetition of the stride kinematics during RSA in elite female eld hockey players. (*) Different from the rst repetition atp< 0.05. Variables Repetition 2 3 4 5 6 Sprint Time 1.0 0.4% 2.1 0.5% * 3.2 0.6% * 3.5 0.8% * 4.1 0.5% * Step Frequency 1.6 0.4% 3.3 0.5% * 3.9 0.7% * 4.4 0.8% * 4.0 0.6% * Step Length 0.6 0.4% 1.3 0.5% 0.9 0.5% 1.1 0.5% 0.1 0.5% The analysis between the sections (0–10 m, 10–20 m, and 20–30 m) showed large differ- ences in sprint time (F1.39= 1198.56,p< 0.001, 2 = 0.99) and step length (F2.24= 1039.43, p< 0.001, 2 = 0.99), and moderate differences in step frequency

* 4.4 0.8% * 4.0 0.6% * Step Length 0.6 0.4% 1.3 0.5% 0.9 0.5% 1.1 0.5% 0.1 0.5% The analysis between the sections (0–10 m, 10–20 m, and 20–30 m) showed large differ- ences in sprint time (F1.39= 1198.56,p< 0.001, 2 = 0.99) and step length (F2.24= 1039.43, p< 0.001, 2 = 0.99), and moderate differences in step frequency (F1.5= 15.65,p< 0.001, 2 = 0.57). Pairwise comparisons (Figure) showed differences ( p< 0.001) between all the sections for sprint time and step length, while step frequency showed higher values in the 10–20 m section.

This study examines stride kinematics and relationships between FVP and RSA performance in elite female field hockey players.