Validity of Real-Time Data Generated by a Wearable Microtechnology Device

Session Rating of Perceived Exertion (sRPE) Load and Training Impulse Are Strongly Correlated to GPS-Derived Measures of External Load in NCAA Division I Women's Soccer Athletes

PURPOSE

The purpose of this study was to determine whether session rating of perceived exertion-derived training load (sRPE-TL) correlates with GPS-derived measures of external load in National Collegiate Athletics Association (NCAA) Division I female soccer athletes.

METHODS

Twenty-one NCAA Division 1 collegiate women's soccer athletes (11 starters, 10 non-starters; 65.1 ± 7.2 kg, 168.4 ± 7.9 cm, 20.3 ± 1.5 yrs) volunteered to take part in this study. Data for this study were collected over the course of 16 weeks during the 2018 NCAA women's soccer season. External load and heart rate (HR) data were collected during each training session and match during the season. At least 30 min after the end of an activity (e.g., match or practice), athletes were prompted to complete a questionnaire reporting their perceived exertion for the session. sRPE-TL was calculated at the end of the season by multiplying perceived exertion by the respective session duration.

RESULTS

sRPE-TL was very strongly correlated with total distance, distance covered in velocity zones 1-3, the number of accelerations in zones 4 and 5, total PlayerLoad™, and PlayerLoad™. For internal load, sRPE-TL correlated very strongly (0.70 ≤ |r| < 0.90) with Edward's and Bannister's TRIMP and strongly (0.50 ≤ |r| < 0.70) with duration spent in in heart rate zones 5 and 6 (80-90% and 90-100% max HR, respectively) while correlations with maximum HR (bpm), mean HR (bpm), and mean HR (%) and sRPE-TL were moderate (0.30 ≤ |r| < 0.50).

CONCLUSIONS

In NCAA Division I women soccer, sRPE-TL is strongly associated with external measures of workload. These relationships were stronger during match play, with acceleration load and total distance exhibiting the strongest relationship with sRPE-TL.

The Duration-specific Peak Average Running Speeds of European Super League Academy Rugby League Match Play

ABSTRACT

Whitehead, S, Till, K, Weaving, D, Dalton-Barron, N, Ireton, M, and Jones, B. Duration-specific peak average running speeds of European Super League Academy rugby league match play. J Strength Cond Res 35(7): 1964-1971, 2021-This study aimed to quantify the duration-specific peak average running speeds of Academy-level rugby league match play, and compare between playing positions. Global positioning system data were collected from 149 players competing across 9 teams during 21 professional Academy (under-19) matches. Players were split into 6 positions: hookers (n = 40), fullbacks (n = 24), halves (n = 47), outside backs (n = 104), middles (n = 118), and backrow forwards (n = 104). Data were extracted and the 10-Hz raw velocity files exported to determine the peak average running speeds, via moving averages of speed (m·min-1), for 10- and 30-second, and 1- to 5- and 10-minute durations. The data were log transformed and analyzed using linear mixed-effect models followed by magnitude-based inferences, to determine differences between positions. Differences in the peak average running speeds are present between positions, indicating the need for position-specific prescription of velocity-based training. Fullbacks perform possibly to most likely greater average running speeds than all other positions, at each duration, except at 10 seconds vs. outside backs. Other differences are duration dependent. For 10 seconds, the average running speed is most likely greater for outside backs vs. the hookers, middles, and backrow forwards, but likely to most likely lower for 10 minutes. Hookers have possibly trivial or lower average speed for 10 seconds vs. middles and backrow forwards, but very likely greater average running speed for 10 minutes. The identified peak average running speeds of Academy-level match play seem similar to previously reported values of senior professional level.

Preparing for an Australian Football League Women's League Season

The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min^-1) and acceleration (m·s^-2), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s^-1). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86-1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73-1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05-3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91-3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process.

“How Am I Going, Coach?”—The Effect of Augmented Feedback During Small-Sided Games on Locomotor, Physiological, and Perceptual Responses

Purpose: To investigate whether providing global positioning system feedback to players between bouts of small-sided games (SSGs) can alter locomotor, physiological, and perceptual responses. Methods: Using a reverse counterbalanced design, 20 male university rugby players received either feedback or no feedback during “off-side” touch rugby SSGs. Eight 5v5, 6 × 4-minute SSGs were played over 4 d. Teams were assigned to a feedback or no-feedback condition (control) each day, with feedback provided during the 2-min between-bouts rest interval. Locomotor, heart rate, and differential rating of perceived exertion of breathlessness and leg-muscle exertion were measured and analyzed using a linear mixed model. Outcomes were reported using effect sizes (ES) and 90% confidence intervals (CI), and then interpreted via magnitude-based decisions. Results: Very likely trivial to unclear differences at all time points were observed in heart rate and differential rating of perceived exertion measures. Possibly to very likely trivial effects were observed between conditions, including total distance (ES = 0.15; 90 CI, −0.03 to 0.34), high-speed distance (ES = −0.07; 90 CI, −0.27 to 0.13), and maximal sprint speed (ES = 0.11; 90% CI, −0.11 to 0.34). All within-bout comparisons showed very likely to unclear differences, apart from possible increases in low-speed distance in bout 2 (ES = 0.23; 90% CI, 0.01 to 0.46) and maximal sprint speed in bout 4 (ES = 0.21; 90% CI, −0.04 to 0.45). Conclusions: In this study, verbal feedback did not alter locomotor, physiological, or perceptual responses in rugby players during SSGs. This may be due to contextual factors (eg, opposition) or the type (ie, distance) or low frequency of feedback provided.

Understanding Player Load: Meanings and Limitations

We present a critical reflection on the mechanical variable Player Load, which is based on acceleration data and commonly used in sports. Our motivation to write this paper came from the difficulties that we encountered in the calculation and interpretation of Player Load using our own data, since we did not use the Catapult Sports equipment, which is a merchandise of the company that proposed this variable. We reviewed existing literature in order to understand Player Load better; we found many inconsistencies in PL calculation methods and in the meanings attached to it. Accordingly, this paper presents a brief discussion on the meanings that have been assigned to Player Load, its limitations, and the lack of clear and complete information about Player Load calculation methods. Moreover, the use of arbitrary units and different practical meanings in the literature has associated Player Load with many physical quantities, thereby resulting in difficulties in determining what Player Load measures within the context of sports. It seems that Player Load is related to the magnitude of changes in acceleration, but not the magnitude of acceleration itself. Therefore, coaches and sports scientists should take this information into account when they use Player Load to prescribe and monitor external loads. We concluded that a deeper discussion of Player Load as a descriptor of external load is warranted in the sports sciences literature.

Validity and Reliability of a Wearable Inertial Sensor to Measure Velocity and Power in the Back Squat and Bench Press

Orange, ST, Metcalfe, JW, Liefeith, A, Marshall, P, Madden, LA, Fewster, CR, and Vince, RV. Validity and reliability of a wearable inertial sensor to measure velocity and power in the back squat and bench press. J Strength Cond Res 33(9): 2398-2408, 2019-This study examined the validity and reliability of a wearable inertial sensor to measure velocity and power in the free-weight back squat and bench press. Twenty-nine youth rugby league players (18 ± 1 years) completed 2 test-retest sessions for the back squat followed by 2 test-retest sessions for the bench press. Repetitions were performed at 20, 40, 60, 80, and 90% of 1 repetition maximum (1RM) with mean velocity, peak velocity, mean power (MP), and peak power (PP) simultaneously measured using an inertial sensor (PUSH) and a linear position transducer (GymAware PowerTool). The PUSH demonstrated good validity (Pearson's product-moment correlation coefficient [r]) and reliability (intraclass correlation coefficient [ICC]) only for measurements of MP (r = 0.91; ICC = 0.83) and PP (r = 0.90; ICC = 0.80) at 20% of 1RM in the back squat. However, it may be more appropriate for athletes to jump off the ground with this load to optimize power output. Further research should therefore evaluate the usability of inertial sensors in the jump squat exercise. In the bench press, good validity and reliability were evident only for the measurement of MP at 40% of 1RM (r = 0.89; ICC = 0.83). The PUSH was unable to provide a valid and reliable estimate of any other criterion variable in either exercise. Practitioners must be cognizant of the measurement error when using inertial sensor technology to quantify velocity and power during resistance training, particularly with loads other than 20% of 1RM in the back squat and 40% of 1RM in the bench press.

3×3 Basketball: Performance Characteristics and Changes During Elite Tournament Competition

PURPOSE

To determine the changes in game performance during tournament play of elite 3×3 basketball.

METHODS

A total of 361 men and 208 women competing in selected international tournaments had game demands assessed by wearable technology (global positioning system, inertial sensor, and heart rate) along with postgame blood lactate and perceived responses. Differences in the means for selected variables between games were compared using magnitude-based inferences and reported with effect size and associated confidence limits (CL), along with the percentage difference (ES; ±90% CL, %difference) of log-transformed data.

RESULTS

No clear differences were seen over a tournament period in PlayerLoad™ or PlayerLoad·minute-1. Tournament competition elicits variable changes between games for all inertial measures. Average peak heart rate was 198 (10) and 198 (9) beats·min-1, and average game heart rate was 164 (12) and 165 (18) beats·min-1 for men and women, respectively, with no change between games. Average game lactate was 6.3 (2.4) and 6.1 (2.2) mmol·L-1 for men and women, respectively. Average game ratings of perceived exertion were 5.7 (2.1) and 5.4 (2.0) AU for men and women, respectively. Although lactate and ratings of perceived exertion were variable between games, there was no difference over a tournament.

CONCLUSIONS

The physical and physiological demands of elite 3×3 games over the duration of a tournament are similar regardless of pool or championship rounds. This may imply that maintaining technical and strategic aspects leads to success rather than minimizing fatigue through superior physical preparation. However, the physiological responses are high; caution is warranted in being underprepared for these demands in tournament play.

The Same Story or a Unique Novel? Within-Participant Principal-Component Analysis of Measures of Training Load in Professional Rugby Union Skills Training

Purpose: To identify which combination metrics of external and internal training load (TL) capture similar or unique information for individual professional players during skills training in rugby union using principal-component (PC) analysis. Methods: TL data were collected from 21 male professional rugby union players across a competitive season. This included PlayerLoad™, total distance, and individualized high-speed distance (>61% maximal velocity; all external TL) obtained from a microtechnology device (OptimEye X4; Catapult Innovations, Melbourne, Australia) that was worn by each player and the session rating of perceived exertion (RPE) (internal TL). PC analysis was conducted on each individual to extract the underlying combinations of the 4 TL measures that best describe the total information (variance) provided by the measures. TL measures with PC loadings (PCL) above 0.7 were deemed to possess well-defined relationships with the extracted PC. Results: The findings show that from the 4 TL measures, the majority of an individual’s TL information (first PC: 55–70%) during skills training can be explained by session RPE (PCL: 0.72–0.95), total distance (PCL: 0.86–0.98), or PlayerLoad (PCL: 0.71–0.98). High-speed distance was the only variable to relate to the second PC (PCL: 0.72–1.00), which captured additional TL information (+19–28%). Conclusions: Findings suggest that practitioners could quantify the TL of rugby union skills training with one of PlayerLoad, total distance, or session RPE plus high-speed distance while limiting omitted information of the TL imposed during professional rugby union skills training.

Gradual vs. Maximal Acceleration: Their Influence on the Prescription of Maximal Speed Sprinting in Team Sport Athletes

The primary purpose of this study was to determine if a difference existed between peak speed attained when performing a sprint with maximal acceleration versus from a gradual build-up. Additionally, this investigation sought to compare the actual peak speed achieved when instructed to reach 75% and 90% of maximum speed. Field sport athletes (n = 21) performed sprints over 60 m under the experimental conditions, and the peak speed was assessed with a radar gun. The gradual build-up to maximum speed (8.30 ± 0.40 m∙s⁻¹) produced the greater peak speed (effect size = 0.3, small) than the maximum acceleration run (8.18 ± 0.40 m∙s⁻¹), and the majority of participants (62%) followed this pattern. For the sub-maximum runs, the actual mean percentage of maximum speed reached was 78 ± 6% for the 75% prescribed run and 89 ± 5% for the 90% prescription. The errors in attaining the prescribed peak speeds were large (~15%) for certain individuals, especially for the 75% trial. Sprint training for maximum speed should be performed with a gradual build-up of speed rather than a maximum acceleration. For sub-maximum interval training, the ability to attain the prescribed target peak speed can be challenging for field sport athletes, and therefore where possible, feedback on peak speeds reached should be provided after each repetition.

The peak duration-specific locomotor demands and concurrent collision frequencies of European Super League rugby

Understanding the most demanding passages of European Super League competition can optimise training prescription. We established positional and match half differences in peak relative distances (m·min^-1) across durations, and the number of collisions, high-speed- and very-high-speed-distance completed in the peak 10 min period. Moving-averages (10 s, 30 s, 1 min, 5 min, 10 min) of instantaneous speed (m·s^-1) were calculated from 25 professional rugby league players during 25 matches via microtechnology. Maximal m·min^-1 was taken for each duration for each half. Concurrently, collisions (n), high-speed- (5 to 7 m·s^-1; m) and very-high-speed-distance (> 7 m·s^-1; m) were coded during each peak 10 min. Mixed-effects models determined differences between positions and halves. Aside from peak 10 s, trivial differences were observed in peak m·min^-1 between positions or halves across durations. During peak 10 min periods, adjustables, full- and outside-backs ran more at high-speed and very-high-speed whilst middle- and edge-forwards completed more collisions. Peak m·min^-1 is similar between positional groups across a range of durations and are maintained between halves of the match. Practitioners should consider that whilst the overall peak locomotor "intensity" is similar, how they achieve this differs between positions with forwards also exposed to additional collision bouts.