The aim of this study was to identify the changes in movement variability and movement velocity during a six-week training period using a resistance horizontal forward–backward task without (NOBALL) or with (BALL) the constraint of catching and throwing a rugby ball in the forward phase. Eleven elite male rugby union players (mean ± SD: age 25.5 ± 2.0 years, height 1.83 ± 0.06 m, body mass 95 ± 18 kg, rugby practice 14 ± 3 years) performed eight repetitions of NOBALL and BALL conditions once a week in a rotational flywheel device. Velocity was recorded by an attached rotary encoder while acceleration data were used to calculate sample entropy (SampEn), multiscale entropy, and the complexity index. SampEn showed no significant decrease for NOBALL (ES = -0.64 ± 1.02) and significant decrease for BALL (ES = -1.71 ± 1.16; p < 0.007) conditions. Additionally, movement velocity showed a significant increase for NOBALL (ES = 1.02 ± 1.05; p < 0.047) and significant increase for BALL (ES = 1.25 ± 1.08; p < 0.025) between weeks 1 and 6. The complexity index showed higher levels of complexity in the BALL condition, specifically in the first three weeks. Movement velocity and complex dynamics were adapted to the constraints of the task after a four-week training period. Entropy measures seem a promising processing signal technique to identify when these exercise tasks should be changed.

Inertial measurement units (IMUs) represent a technology that is booming in sports right now. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically to evaluate a magnet-based timing system (M-BTS) for timing short-duration sports actions using the magnetometer built into an IMU in different sporting contexts. Forty-eight athletes (22.7 ± 3.3 years, 72.2 ± 10.3 kg, 176.9 ± 8.5 cm) and eight skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg) performed a 60-m linear sprint running test and a ski slalom, respectively. The M-BTS consisted of placing several magnets along the course in both contexts. The magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. The time between peaks was calculated. The system was validated with photocells. The 95% error intervals for the total times were less than 0.077 s for the running test and 0.050 s for the ski slalom. With the M-BTS, future studies could select and cut the signals belonging to the other sensors that are integrated in the IMU, such as the accelerometer and the gyroscope.

Introduction: The inclusion of sport-specific constraints in resistance training promotes the development of player abilities in an integrated way, which maximises the effectiveness of player adaptations induced by training. Considering that perceptual-cognitive abilities play a fundamental role in football, decision making could be introduced to enhance the cognitive similarity of resistance tasks to sport actions. However, it is unknown how decision making as a constraint could affect the player during an elastic resistance task. Therefore, the aim of this study was to investigate the effects of decision making of high-level female football players on movement variability and performance during an elastic band resistance task.Methods: Twenty-three high-level female football players performed the elastic resistance task with a ball, both as attackers and as defenders without decision making (NDM) and with decision making (DM). The movement variability was quantified using the sample entropy derived from the acceleration recorded with an accelerometer placed at the lower back of each player. The passing accuracy of the attacker was quantified using a scoring scale.Results: Results revealed that adding decision making to an elastic resistance task increased the movement variability of the defender but did not affect the movement variability of the attacker. In contrast, the passing accuracy of the attacker was reduced. Overall, the attacker had a higher movement variability compared to the defender.Discussion: These findings suggest that decision making, as a football-specific constraint, can enhance the potential of an elastic resistance task in training. This is due to the fact that it reduces control and regularity of movement for the defensive role player and increases technical difficulty for the attacking role player. Furthermore, these effects are beneficial, as they can promote the adaptive processes necessary to optimise the performance of the players.

The aim of this study was to determine whether whole body vibration increases movement variability while performing a half squat with different ballasts and rhythms through entropy. A total of 12 male athletes (age: 21.24 ± 2.35 years, height: 176.83 ± 5.80 cm, body mass: 70.63 ± 8.58 kg) performed a half squat with weighted vest, dumbbells and bar with weights suspended with elastic bands, with and without vibration at the squat rhythm of 40 and 60 bpm. Each ballast corresponded to 15% of the body mass. The movement variability was analysed by calculating the sample entropy of the acceleration signal, recorded at the waist using an accelerometer. With vibration, differences were found between weighted vest and dumbbells (t(121) = -8.81, p < 0.001 at 40 bpm; t(121) = -8.18, p < 0.001 at 60 bpm) and between weighted vest and bar at both rhythms (t(121) = -8.96, p < 0.001 at 40 bpm; t(121) = -8.83, p < 0.001 at 60 bpm). Furthermore, a higher sample entropy was obtained at 40 bpm with all ballasts (t(121) = 5.65, p < 0.001 with weighted vest; t(121) = 6.27, p < 0.001 with dumbbells; t(121) = 5.78, p < 0.001 with bar). No differences were found without vibration. These findings reveal that adding mechanical vibration to a half squat produces a non-proportional increase in movement variability, being larger when the ballast is placed on the upper limbs and when performed at a slow rhythm.

The aim of this study was to assess and compare performance and movement variability (MV) in both bilateral and unilateral vertical drop jumps (DVJs) under conditions involving the incorporation or exclusion of ball catching. Twelve amateur basketball players were recruited for participation in the study (seven females and five males). Participants performed three jumps in each of the six conditions analyzed in randomized order: bilateral DVJ without (BNB) and with ball (BB); unilateral DVJ right leg without (RNB) and with ball (RB); and unilateral DVJ left leg without (LNB) and with ball (LB). MV and DVJ performance parameters were analyzed with an accelerometer and a force platform. MV was quantified using the sample entropy (sample entropy; SampEn) derived from the acceleration of the lower back. Differences between the different DVJ conditions were determined with the Wilcoxon test, with a significance level set at p < 0.05. The comparisons were also assessed via standardized mean differences (Cohen’s d). No significant differences were observed in jump height, contact time and reactive strength index between conditions. However, the RB condition reported higher MV compared to RNB (effect size = 0.79; p = 0.016). Similarly, LNB showed greater MV compared to RNB (effect size = −0.62; p = 0.042). The inclusion of the ball in the DVJ increased the MV in the bilateral condition and in the right leg, but not in the unilateral condition with the left leg. The asymmetry between legs (right vs. left) in MV values in NOBALL conditions was higher (≈15%) compared to the BALL condition (≈5%).

Several microtechnology devices quantify the external load of team sports using Global Positioning Systems sampling at 5, 10, or 15 Hz. However, for short, explosive actions, such as collisions, these sample rates may be limiting. It is known that very high-frequency sampling is capable of capturing changes in actions over a short period of time. Therefore, the aim of this study was to compare the mean acceleration and entropy values obtained from 100 Hz and 1000 Hz tri-axial accelerometers in tackling actions performed by rugby players. A total of 11 elite adolescent male rugby league players (mean ± SD; age: 18.5 ± 0.5 years; height: 179.5 ± 5.0 cm; body mass: 88.3 ± 13.0 kg) participate in this study. Participants performed tackles (n = 200), which were recorded using two triaxial accelerometers sampling at 100 Hz and 1000 Hz, respectively. The devices were placed together inside the Lycra vests on the players’ backs. The mean acceleration, sample entropy (SampEn), and approximate entropy (ApEn) were analyzed. In mean acceleration, the 1000 Hz accelerometer obtained greater values (p < 0.05). However, SampEn and ApEn were greater with the 100 Hz accelerometer (p < 0.05). A large relationship was observed between the two devices in all the parameters analyzed (R² > 0.5; p < 0.0001). Sampling frequency can affect the quality of the data collected, and a higher sampling frequency potentially allows for the collection of more accurate motion data. A frequency of 1000 Hz may be suitable for recording short and explosive actions.