Ruf, L, Chéry, C, Taylor, KL. Validity and reliability of the load-velocity relationship to predict the 1RM in deadlift. J Strength Cond Res 32(3): 681-689, 2018-The aim of this study was to verify the reliability and validity of using submaximal loads from the load-velocity relationship to predict the actual 1 repetition maximum (1RM) in the deadlift. Data from 11 resistance-trained athletes were analyzed performing three 1RM assessments separated by at least 3 days. Reliability was assessed by comparing predicted 1RMs of sessions 2 and 3, whereas for validity purposes, predicted 1RMs of session 3 were compared with actual 1RMs of session 2. Mean concentric velocity at 1RM (v at 1RM) was entered in individualized linear regression equations, derived from the load-velocity relationship for 3 (20-60%, 40-80%, and 60-90% of 1RM), 4 (20-80% and 40-90% of 1RM), and 5 (20-90% of 1RM) incremental loads to predict 1RMs. There were trivial changes for all predicted 1RMs between sessions with 20-90% of 1RM being the most reliable model. Similarly, the actual 1RM was very stable (effect size [ES] = 0.04, 90% confidence limit [CL] [-0.03 to 0.12], typical error of measurement [TE] = 3.4 kg [2.5-5.4], intraclass coefficient [ICC] = 0.99 [0.96-0.996], and coefficient of variation [CV] = 1.9% [1.4-3.0]), whereas the v at 1RM was unreliable between trials (ES = -0.30, 90% CL [-0.78 to 0.17], TE = 0.029 m·s [0.022-0.047], ICC = 0.63 [0.19-0.86], and CV = 15.7% [11.7-26.1]). However, predicted 1RMs computed from all submaximal load ranges substantially overestimated the actual 1RM with considerable differences between athletes. Although 1RM predictions showed high reliability, they all overestimated the actual 1RM, which was stable between sessions. Therefore, it is not recommended to apply the prediction models used in this study to compute daily 1RMs.

The purpose of this study was to examine to what extent the physical match performance of professional soccer players is both position and player specific. First, official match data from the 2019/20 German Bundesliga season was used to search for players that met the inclusion criteria of playing a minimum of four entire matches in at least two different playing positions. Overall, 25 players met the criteria prior to the COVID-19 induced break, playing a minimum of eight matches. Second, the physical match performance of these players was analyzed separately for each position they played. The following four parameters were captured: total distance, high-intensity distance, sprinting distance, and accelerations. Third, the 25 players’ physical match performance data was then compared to normative data for each position they played to understand whether players adapted their physical performance (position dependent), or maintained their performance regardless of which position they were assigned to (position independent). When switching the position, the change in physical match performance of the respective players could be explained by 44–58% through the normative positional data. Moreover, there existed large individual differences in the way players adapted or maintained their performance when acting in different positions. Coaches and practitioners should be aware that some professional soccer players will likely incur differences in the composition of physical match performance when switching positions and therefore should pay special consideration for such differences in the training and recovery process of these players.

Chéry, C and Ruf, L. Reliability of the load-velocity relationship and validity of the PUSH to measure velocity in the deadlift. J Strength Cond Res 33(9): 2370–2380, 2019—This study investigated the reliability between load and mean velocity, mean propulsive velocity, peak velocity, mean power, and peak power in the deadlift. Also, we looked at the validity of an inertial sensor (PUSH) and a linear-position transducer (Tendo) to measure velocity variables. Ten strength-trained men (23.4 ± 1.3 years) were involved in three 1 repetition maximum (1RM) testing sessions, separated by at least 72 hours. The protocol used 6 different lifting intensities, comprising 20, 40, 60, 80, 90, and 100% of 1RM. Reliability of the load-velocity and load-power relationship was assessed by comparing velocity and power measurements from session 2 and 3 for each relative %1RM. The validity of tested devices was analyzed regarding to each relative intensity by comparing results from each instrument to a reference instrument (GymAware). The findings revealed that intermediate intensities (ranging from 60 to 90% of 1RM) seem to be reliable. Furthermore, extreme points of the load-velocity curve (20, 40, and 100% of 1RM) were found to be less reliable and should therefore be used with caution when implemented as part of autoregulating strategies. Tendo produced measurements that were highly correlated with GymAware and thus, constitutes a valid and cheaper alternative. By contrast, measurements from the PUSH presented a low level of precision and accuracy. Therefore, PUSH cannot be considered as a valid tool to measure velocity variables in the deadlift.

Introduction: Maximal aerobic speed (MAS), usually measured by cardiopulmonary exercise testing (CPET) on a treadmill, is gaining popularity in soccer to determine aerobic performance. Several field tests are used to estimate MAS, although, gold standard methods are still not clarified. Therefore, this work aims 1) to compare two different CPET based methods to assess MAS and 2) to investigate the convergent validity of two common field tests to estimate MAS in soccer.Methods: Thirteen trained male soccer players completed an CPET on a treadmill to determine two VO2-kinetic based definitions of MAS (MASPlateau = speed at onset of VO2-plateau = gold standard; MAS30s = first speed of 30-s-interval of VO2max), the Université de Montreal Track Test (UMTT; VUMTT = speed of the last stage), and a 1500-m-time trial (1500-m-TT; V1500m = average speed). MASPlateau, MAS30s, VUMTT, and V1500m were compared using ANOVA. Additionally, limits of agreement analysis (LoA), Pearson’s r, and ICC were calculated between tests.Results: MAS30s, VUMTT, and V1500m significantly overestimated MASPlateau by 0.99 km/h (ES = 1.61; p < 0.01), 1.61 km/h (ES = 2.03; p < 0.01) and 1.68 km/h (ES = 1.77; p < 0.01), respectively, with large LoA (-0.21 ≤ LoA≤3.55), however with large-to-very large correlations (0.65 ≤ r ≤ 0.87; p ≤ 0.02; 0.51 ≤ ICC≤ 0.85; p ≤ 0.03).Discussion: The overestimation and large LoA of MASPlateau by all estimates indicate that 1) a uniform definition of MAS is needed and 2) the UMTT and a 1500-m-TT seem questionable for estimating MAS for trained soccer players on an individual basis, while regression equations might be suitable on a team level. The results of the present work contribute to the clarification of acquisition of MAS in soccer.

Load monitoring is considered important to manage the physical training process in team sports such as Association Football. Previous studies have described the load monitoring practices of elite English football clubs and clubs with an established sports-science department. An examination of a broader international sample is currently not available. In addition, previous research has suggested factors that may improve the implementation of load monitoring practices, such as a strong club belief on the benefit of evidence-based practice (EBP) and high club financial resources. However, no study has examined yet the actual impact of these factors on the monitoring practices. Therefore, this study aims (1) to provide an overview of load monitoring practices in European elite football and (2) to provide insight into the differences in implementation between clubs by examining the impact of the club beliefs on the benefit of EBP and the club financial resources. An online survey, consisting of multiple choice and Likert scale questions, was distributed among sports-science and sports-medicine staff (n = 99, 50% response rate). Information was asked about the types of data collected, collection purposes, analysis methods, and staff involvement. The results indicated that external load data (e.g., global navigation satellite system, accelerometer…) was collected the most whilst respondents also indicated to collect internal load (e.g., heart rate, rating of perceived exertion…) and training outcome data (e.g., aerobic fitness, neuromuscular fatigue…) for multiple purposes. Considerable diversity in data analysis was observed suggesting that analysis is often limited to reporting the gathered data. Sports-science staff were responsible for data collection and analysis. Other staff were involved in data discussion to share decision-making. These practices were positively impacted by a stronger club belief on the benefit of EBP and greater financial resources. Creating an organizational culture, characterized by a strong belief on the benefit of EBP, is important to increase the impact of load monitoring. However, the actual potential may still be largely determined by financial resources. High-level clubs could therefore play a leading role in generating and sharing knowledge to improve training practices and player health.

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