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We examined the effects of repeated sprint training (RST) session volume on acute physiological, neuromuscular, perceptual and performance outcomes. In a randomised, counterbalanced, and crossover design, 14 healthy and trained male and female athletes (age: 23 ± 3 years) completed two sets of 10 × 40 m (10 × 40), 5 × 40 m (5 × 40), 10 × 20 m (10 × 20) and 5 × 20 m (5 × 20) sprints with 30 s rest between repetitions and 3 min rest between sets for all protocols. Average and peak heart rate, average oxygen consumption (VO 2 ), time >90% of maximal oxygen consumption (VO 2max ), differential ratings of perceived exertion (RPE), session-RPE training load (sRPE-TL), percentage sprint decrement (S dec ), acceleration load and distance >90% of maximal sprint speed were recorded during each session. Neuromuscular performance (i.e. countermovement jump, lower-limb stiffness and isometric hamstring strength) were measured post-session, 24 h, and 48 h and compared to pre-session. A univariate analysis of variance was used to compare within- and between-protocol differences. To aid data interpretation, all effects were expressed as an effect size and accompanied by probability values (p MET ). The 10 × 40 protocol induced the greatest training load compared to all other protocols (p MET  < 0.05), including moderate to very large differences in breathlessness RPE, large differences in S dec and time >90% VO 2max and very large differences in sRPE-TL. The 5 × 20 protocol induced the lowest training load compared to all other protocols (p MET  < 0.05), including moderate to large differences in sRPE-TL and leg muscle RPE. Heart rate, VO 2 , sRPE-TL, leg muscle RPE and S dec were similar between 5 × 40 and 10 × 20 (p MET  < 0.05), but the acceleration load was greater for 10 × 20 when compared to 5 × 40 (p MET  < 0.001), and this difference was large. Changes in neuromuscular performance across all timepoints and all protocols were unclear. Larger session volumes increase the demands of RST and by manipulating volume, sprint distance and the number of repetitions, practitioners can alter the internal and external training load., (© 2024 The Author(s). European Journal of Sport Science published by Wiley‐VCH GmbH on behalf of European College of Sport Science.)

Background: Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions., Objectives: We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors., Methods: This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [ V ˙ O 2 max], 51.9 ± 7.2 mL/kg/min), the validation study included 21 cyclists (seven female; V ˙ O 2 max 53.5 ± 11.0 mL/kg/min), 20 runners (six female; V ˙ O 2 max 57.5 ± 7.2 mL/kg/min), and 18 kayakers (five female; V ˙ O 2 max 45.6 ± 4.8 mL/kg/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O 2 lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (R 2 ) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration., Results: Very-large to near-perfect within-subject correlations (r = 0.76-0.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (R 2  = 0.77-0.96) and displayed good accuracy (mean absolute error; CHO = 16-21 g [10-14%], EE = 53-82 kcal [7-11%]). In the validation study, the mean absolute error ranged from 16-50 g [15-45%] for CHO models to 53-182 kcal [9-31%] for EE models. The calibrated mean absolute error ranged from 9-20 g [8-18%] for CHO models to 36-72 kcal [6-12%] for EE models., Conclusions: At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment., (© 2024. The Author(s).)

Objectives: To evaluate the criterion and longitudinal validity of field- and laboratory-derived heart rate (HR) indices of resting and submaximal fitness tests (SMFTs) as measures of cardiorespiratory fitness., Design: Observational, repeated measures., Methods: Twenty-nine semi-professional footballers participated. Laboratory assessments took place at the start and end of a preseason training period, whereby resting, SMFT HR-derived indices, and criterion measures of cardiorespiratory fitness (running economy [RE], maximal oxygen uptake [V̇O 2 max] and aerobic speed [MAS]) were collected. Throughout this training period, two field-based SMFT protocols, prescribed at different intensities, were administered weekly. Individual slopes were calculated from the analysis of within-athlete change scores. Associations between laboratory and field measures were assessed via Pearson's correlation coefficient (r) and linear regression models., Results: Relationships between SMFT HR-derived indices from laboratory and field were very-large for exercise HR (r = 0.74 to 0.87) and moderate to very-large for HR recovery (0.43 to 0.76). Moderate to very-large inverse relationships were observed between exercise HR and HR recovery with V̇O 2 max and MAS (-0.41 to -0.78), whereas resting HR showed no substantial relationships. Changes in exercise HR showed large and very-large inverse correlations with preseason changes in V̇O 2 max (-0.54 to -0.60) and MAS (-0.64 to -0.83). Relationships between changes in HR recovery and maximal cardiorespiratory criterion measures were moderate to large (-0.32 to -0.63)., Conclusion: SMFT exercise HR is a valid proxy measure of cardiorespiratory fitness irrespective of test setting, whereas the validity of HRR remains elusive and appears to vary between exercise intensities., Competing Interests: Declaration of interest statement None., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Repeated-sprint training (RST) is a common training method for enhancing physical fitness in athletes. To advance RST prescription, it is important to understand the effects of programming variables on physical fitness and physiological adaptation., Objectives: This study (1) quantifies the pooled effects of running RST on changes in 10 and 20 m sprint time, maximal oxygen consumption (VO 2max ), Yo-Yo Intermittent Recovery Test Level 1 (YYIR1) distance, repeated-sprint ability (RSA), countermovement jump (CMJ) height and change of direction (COD) ability in athletes, and (2) examines the moderating effects of program duration, training frequency, weekly volume, sprint modality, repetition distance, number of repetitions per set and number of sets per session on changes in these outcome measures., Methods: Pubmed, SPORTDiscus and Scopus databases were searched for original research articles up to 04 July 2023, investigating RST in healthy, able-bodied athletes, between 14 and 35 years of age, and a performance calibre of trained or above. RST interventions were limited to repeated, maximal running (land-based) sprints of ≤ 10 s duration, with ≤ 60 s recovery, performed for 2-12 weeks. A Downs and Black checklist was used to assess the methodological quality of the included studies. Eligible data were analysed using multi-level mixed-effects meta-analysis, with standardised mean changes determined for all outcomes. Standardised effects [Hedges G (G)] were evaluated based on coverage of their confidence (compatibility) intervals (CI) using a strength and conditioning specific reference value of G = 0.25 to declare an improvement (i.e. G > 0.25) or impairment (i.e. G < - 0.25) in outcome measures. Applying the same analysis, the effects of programming variables were then evaluated against a reference RST program, consisting of three sets of 6 × 30 m straight-line sprints performed twice per week for 6 weeks (1200 m weekly volume)., Results: 40 publications were included in our investigation, with data from 48 RST groups (541 athletes) and 19 active control groups (213 athletes). Across all studies, the effects of RST were compatible with improvements in VO 2max (G 0.56, 90% CI 0.32-0.80), YYIR1 distance (G 0.61, 90% CI 0.43-0.79), RSA decrement (G - 0.61, 90% CI - 0.85 to - 0.37), linear sprint times (10 m: G - 0.35, 90% CI - 0.48 to - 0.22; 20 m: G - 0.48, 90% CI - 0.69 to - 0.27), RSA average time (G - 0.34, 90% CI - 0.49 to - 0.18), CMJ height (G 0.26, 90% CI 0.13-0.39) and COD ability (G - 0.32, 90% CI - 0.52 to - 0.12). Compared with the reference RST program, the effects of manipulating training frequency (+ 1 session per week), program duration (+ 1 extra training week), RST volume (+ 200 m per week), number of reps (+ 2 per set), number of sets per session (+ 1 set) or rep distance (+ 10 m per rep) were either non-substantial or comparable with an impairment in at least one outcome measure per programming variable., Conclusions: Running-based RST improves speed, intermittent running performance, VO 2max , RSA, COD ability and CMJ height in trained athletes. Performing three sets of 6 × 30 m sprints, twice per week for 6 weeks is effective for enhancing physical fitness and physiological adaptation. Additionally, since our findings do not provide conclusive support for the manipulation of RST variables, further work is needed to better understand how programming factors can be manipulated to augment training-induced adaptations., Study Registration: Open Science Framework registration https://doi.org/10.17605/OSF.IO/RVNDW ., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Submaximal fitness test (SMFT) outcome measures are frequently collected with a wide array of technologies and methodological approaches., Purpose: To examine the test-retest reliability of various SMFT outcome measures derived from different protocols and analytical techniques., Methods: Twenty-six semiprofessional adult soccer players performed 3 SMFT protocols, including 2 continuous (3 min, 11 and 12.8 km·h-1) and 1 intermittent (4 × 50 m, 18 km·h-1) twice, each separated by 7 days. Heart-rate (HR) indices (exercise HR, HR recovery) and scapula-mounted (PlayerLoad vector magnitude) and foot-mounted (flight time and contact time, stride length) microelectrical mechanical system-derived variables were collected using different time frames and analytical approaches adopted in the literature and practice. Absolute reliability was quantified as the group mean difference, typical error of measurement, also expressed as the coefficient of variation (where appropriate) and standardized units (ie, d). Intraclass correlation coefficient was used to quantify relative reliability., Results: The highest degrees of reliability were evident for exercise HR (typical error: 1.0%-1.6% points), the vertical component of PlayerLoad (expressed in arbitrary units; coefficient of variation: 5.5%-7.0%), and contact time (coefficient of variation: 1.5%-3.0%). These estimates were not influenced by SMFT protocol or analytical approach. All other measures displayed poorer reliability and/or were different between protocols and analytical methods., Conclusions: SMFT protocols impact the test-retest reliability of various outcome measures; however, exercise HR, vertical PlayerLoad, and contact time (derived from foot-mounted micro-electrical mechanical systems) appear to have stable measurement properties to assist the assessment of aerobic capacity and lower-limb neuromuscular status, respectively.

Various terms used in sport and exercise science, and medicine, are derived from other fields such as epidemiology, pharmacology and causal inference. Conceptual and nomological frameworks have described training load as a multidimensional construct manifested by two causally related subdimensions: external and internal training load. In this article, we explain how the concepts of training load and its subdimensions can be aligned to classifications used in occupational medicine and epidemiology, where exposure can also be differentiated into external and internal dose. The meanings of terms used in epidemiology such as exposure, external dose, internal dose and dose-response are therefore explored from a causal perspective and their underlying concepts are contextualised to the physical training process. We also explain how these concepts can assist in the validation process of training load measures. Specifically, to optimise training (i.e. within a causal context), a measure of exposure should be reflective of the mediating mechanisms of the primary outcome. Additionally, understanding the difference between intermediate and surrogate outcomes allows for the correct investigation of the effects of exposure measures and their interpretation in research and applied settings. Finally, whilst the dose-response relationship can provide evidence of the validity of a measure, conceptual and computational differentiation between causal (explanatory) and non-causal (descriptive and predictive) dose-response relationships is needed. Regardless of how sophisticated or "advanced" a training load measure (and metric) appears, in a causal context, if it cannot be connected to a plausible mediator of a relevant response (outcome), it is likely of little use in practice to support and optimise the training process., (© 2023. The Author(s).)

Background: Repeated-sprint training (RST) involves maximal-effort, short-duration sprints (≤ 10 s) interspersed with brief recovery periods (≤ 60 s). Knowledge about the acute demands of RST and the influence of programming variables has implications for training prescription., Objectives: To investigate the physiological, neuromuscular, perceptual and performance demands of RST, while also examining the moderating effects of programming variables (sprint modality, number of repetitions per set, sprint repetition distance, inter-repetition rest modality and inter-repetition rest duration) on these outcomes., Methods: The databases Pubmed, SPORTDiscus, MEDLINE and Scopus were searched for original research articles investigating overground running RST in team sport athletes ≥ 16 years. Eligible data were analysed using multi-level mixed effects meta-analysis, with meta-regression performed on outcomes with ~ 50 samples (10 per moderator) to examine the influence of programming factors. Effects were evaluated based on coverage of their confidence (compatibility) limits (CL) against elected thresholds of practical importance., Results: From 908 data samples nested within 176 studies eligible for meta-analysis, the pooled effects (± 90% CL) of RST were as follows: average heart rate (HR avg ) of 163 ± 9 bpm, peak heart rate (HR peak ) of 182 ± 3 bpm, average oxygen consumption of 42.4 ± 10.1 mL·kg -1 ·min -1 , end-set blood lactate concentration (B[La]) of 10.7 ± 0.6 mmol·L -1 , deciMax session ratings of perceived exertion (sRPE) of 6.5 ± 0.5 au, average sprint time (S avg ) of 5.57 ± 0.26 s, best sprint time (S best ) of 5.52 ± 0.27 s and percentage sprint decrement (S dec ) of 5.0 ± 0.3%. When compared with a reference protocol of 6 × 30 m straight-line sprints with 20 s passive inter-repetition rest, shuttle-based sprints were associated with a substantial increase in repetition time (S avg : 1.42 ± 0.11 s, S best : 1.55 ± 0.13 s), whereas the effect on sRPE was trivial (0.6 ± 0.9 au). Performing two more repetitions per set had a trivial effect on HR peak (0.8 ± 1.0 bpm), B[La] (0.3 ± 0.2 mmol·L -1 ), sRPE (0.2 ± 0.2 au), S avg (0.01 ± 0.03) and S dec (0.4; ± 0.2%). Sprinting 10 m further per repetition was associated with a substantial increase in B[La] (2.7; ± 0.7 mmol·L -1 ) and S dec (1.7 ± 0.4%), whereas the effect on sRPE was trivial (0.7 ± 0.6). Resting for 10 s longer between repetitions was associated with a substantial reduction in B[La] (-1.1 ± 0.5 mmol·L -1 ), S avg (-0.09 ± 0.06 s) and S dec (-1.4 ± 0.4%), while the effects on HR peak (-0.7 ± 1.8 bpm) and sRPE (-0.5 ± 0.5 au) were trivial. All other moderating effects were compatible with both trivial and substantial effects [i.e. equal coverage of the confidence interval (CI) across a trivial and a substantial region in only one direction], or inconclusive (i.e. the CI spanned across substantial and trivial regions in both positive and negative directions)., Conclusions: The physiological, neuromuscular, perceptual and performance demands of RST are substantial, with some of these outcomes moderated by the manipulation of programming variables. To amplify physiological demands and performance decrement, longer sprint distances (> 30 m) and shorter, inter-repetition rest (≤ 20 s) are recommended. Alternatively, to mitigate fatigue and enhance acute sprint performance, shorter sprint distances (e.g. 15-25 m) with longer, passive inter-repetition rest (≥ 30 s) are recommended., (© 2023. Crown.)

Purpose: To survey team-sport practitioners on current practices and perceptions of submaximal fitness tests (SMFTs)., Methods: A convenience sample of team-sport practitioners completed an online survey (September to November 2021). Descriptive statistics were used to obtain information of frequencies. A mixed-model quantile (median) regression was employed to assess the differences between the perceived influence of extraneous factors., Results: A total of 66 practitioners (74 discrete protocols) from 24 countries completed the survey. Time-efficient and nonexhaustive nature were considered the most important features of implementation. Practitioners prescribed a range of SMFTs, administered mostly on a monthly or weekly basis, but scheduling strategies appeared to differ across SMFT categories. Cardiorespiratory/metabolic outcome measures were collected in most protocols (n = 61; 82%), with the majority monitoring heart-rate-derived indices. Subjective outcome measures (n = 33; 45%) were monitored exclusively using ratings of perceived exertion. Mechanical outcome measures (n = 19; 26%) included either a combination of locomotor outputs (eg, distance covered) or variables derived from microelectrical mechanical systems. The perceived influence of extraneous factors on measurement accuracy varied according to outcome measure, and there was a lack of consensus among practitioners., Conclusions: Our survey showcases the methodological frameworks, practices, and challenges of SMFTs in team sports. The most important features for implementation perhaps support the use of SMFTs as a feasible and sustainable tool for monitoring in team sports. The wide variety of protocols, scheduling strategies, and outcome measures, along with their associated collection and analytical techniques, may reflect the absence of robust evidence regarding the application of SMFTs in team sports.

Background: Submaximal fitness tests (SMFT) are a pragmatic approach for evaluating athlete's physiological state, due to their time-efficient nature, low physiological burden and relative ease of administration in team sports settings. While a variety of outcome measures can be collected during SMFT, exercise heart rate (HRex) is the most popular. Understanding the measurement properties of HRex can support the interpretation of data and assist in decision making regarding athlete's current physiological state and training effects., Objectives: The aims of our systematic review and meta-analysis were to: (1) establish meta-analytic estimates of SMFT HRex reliability and convergent validity and (2) examine the moderating influence of athlete and protocol characteristics on the magnitude of these measurement properties., Methods: We conducted a systematic literature search with MEDLINE, Scopus and Web of Science databases for studies published up until January 2022 since records began. Studies were considered for inclusion when they  included team sports athletes and the reliability and/or convergent validity of SMFT HRex was investigated. Reliability statistics included the group mean difference (MD), typical error of measurement (TE) and intraclass correlation coefficient (ICC) derived from test-retest(s) designs. Pearson's correlation coefficient (r) describing the relationship between SMFT HRex and a criterion measure of endurance performance was used as the statistic for convergent validity. Qualitative assessment was conducted using risk of bias assessment tool for non-randomised studies. Mixed-effects, multilevel hierarchical models combined with robust variance estimate tests were performed to obtain pooled measurement property estimates, effect heterogeneity, and meta-regression of modifying effects., Results: The electronic search yielded 21 reliability (29 samples) and 20 convergent validity (29 samples) studies that met the inclusion criteria. Reliability meta-analysis indicated good absolute (MD = 0.5 [95% CI 0.1 to 0.9] and TE = 1.6 [95% CI 1.4 to 1.9] % points), and high relative (ICC = 0.88 [95% CI 0.84 to 0.91]) reliability. Convergent validity meta-analysis indicated an inverse, large relationship (r = - 0.58 [95% CI - 0.62 to - 0.54]) between SMFT HRex and endurance tests performance. Meta-regression analyses suggested no meaningful influence of SMFT protocol or athlete characteristics on reliability or convergent validity estimates., Conclusions: Submaximal fitness test HRex is a reliable and valid proxy indicator of endurance performance in team sport athletes. Athlete and SMFT protocol characteristics do not appear to have a meaningful effect on these measurement properties. Practitioners may implement SMFT HRex for monitoring athlete's physiological state by using our applied implications to guide the interpretation of data in practice. Future research should examine the utility of SMFT HRex to track within-athlete changes in aerobic capacity, as well as any further possible effects of SMFT protocols design elements or HRex analytical methods on measurement properties. Registration Protocol registration can be found in Open Science Framework and available through https://doi.org/10.17605/OSF.IO/9C2JV ., (© 2023. The Author(s).)

Purpose: To examine the construct validity and reliability of 2 single items for fatigue and recovery in dancers. The construct validity was assessed using reference instruments: the fatigue items of the Brunel Mood Scale (BRUMS) and the Short Recovery and Stress Scale (SRSS). A secondary aim was to explore the respondent interpretation of these 2 items using a concept identification approach., Methods: Two hundred forty-three (N = 243) dancers completed single-item fatigue and recovery (unipolar and bipolar), BRUMS, and SRSS once for construct validity. For reliability, 49 dancers completed the questionnaires twice, 1 week apart. Using a concept identification approach, 49 dancers were also asked comprehension and interpretation of fatigue and recovery., Results: The fatigue item correlated with SRSS stress items (rs = .37-.51) and BRUMs fatigue items (rs = .63-.66). The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference (rs = .39-.43). Reliability was confirmed for the single items of fatigue (κ = .77-.78) and recovery (κ = .71-.78). Main responses for the concept of fatigue were tiredness (34.7%), muscle soreness (17.3%), and energy (13.0%). Main responses for the concept of recovery were muscle soreness (43.0%), tiredness (27.9%), and fatigue (24.0%)., Conclusion: We provide preliminary confirmation of the validity and reliability of the single item fatigue in dancers. The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference, but did display acceptable reliability and agreement. Further research is warranted further exploring other measurement properties.

Background: Sided games (i.e., small sided, medium sided, large sided) involve tactical, technical, physical, and psychological elements and are commonly implemented in soccer training. Although soccer sided-games research is plentiful, a meta-analytical synthesis of external load exposure during sided games is lacking., Objective: The objective of this systematic review and meta-analysis was to: (1) synthesize the evidence on high-speed and sprint running exposure induced by sided games in adult soccer players, (2) establish pooled estimates and intra-individual reliability for high-speed and sprint running exposure, and (3) explore the moderating effects of game format and playing constraints., Methods: A literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Four databases (PubMed/MEDLINE, Scopus, SPORTDiscus, Web of Science Core Collection) were systematically searched up to 25 January, 2022. Eligibility criteria were adult soccer players (population); training programs incorporating sided games (intervention); game manipulations including number of players, pitch dimension, and game orientation (comparator); and high-speed, very high-speed, and sprint relative (m[Formula: see text]min -1 ) running distances and associated intra-individual reliability (outcome). Eligible study risk of bias was evaluated using RoBANS. Pooled estimates for high-speed and sprint running exposure, and their intra-individual reliability, along with the moderating effect of tracking device running velocity thresholds, pitch dimension (i.e., area per player), and game orientation (i.e. score or possession), were determined via a multi-level mixed-effects meta-analysis. Estimate uncertainty is presented as 95% compatibility intervals (CIs) with the likely range of relative distances in similar future studies determined via 95% prediction intervals., Results: A total of 104 and 7 studies met our eligibility criteria for the main and reliability analyses, respectively. The range of relative distances covered across small-sided games, medium-sided games, and large-sided games was 14.8 m[Formula: see text]min -1 (95% CI 12.3-17.4) to 17.2 m[Formula: see text]min -1 (95% CI 13.5-20.8) for high-speed running, 2.7 m[Formula: see text]min -1 (95% CI 1.8-3.5) to 3.6 m[Formula: see text]min -1 (95% CI 2.3-4.8) for very high-speed running, and 0.2 m[Formula: see text]min -1 (95% CI 0.1-0.4) to 0.7 m[Formula: see text]min -1 (95% CI 0.5-0.9) for sprinting. Across different game formats, 95% prediction intervals showed future exposure for high-speed, very high-speed running, and sprinting to be 0-46.5 m[Formula: see text]min -1 , 0-14.2 m[Formula: see text]min -1 , and 0-2.6 m[Formula: see text]min -1 , respectively. High-speed, very high-speed running, and sprinting showed poor reliability with a pooled coefficient of variation of 22.8% with distances being moderated by device speed thresholds, pitch dimension, and game orientation., Conclusions: This review is the first to provide a detailed synthesis of exposure and intra-individual reliability of high-speed and sprint running during soccer sided games. Our estimates, along with the moderating influence of common programming variables such as velocity thresholds, area per player, and game orientation should be considered for informed planning of small-sided games, medium-sided games, and large-sided games soccer training., Clinical Trial Registration: Open Science Framework available through https://osf.io/a4xr2/ ., (© 2022. The Author(s).)

Goal and Theoretical Commentary: A number of recent life cycle assessment (LCA) studies have concluded that animal-sourced foods should be restricted-or even avoided-within the human diet due to their relatively high environmental impacts (particularly those from ruminants) compared with other protein-rich foods (mainly protein-rich plant foods). From a nutritional point of view, however, issues such as broad nutrient bioavailability, amino acid balances, digestibility and even non-protein nutrient density (e.g., micronutrients) need to be accounted for before making such recommendations to the global population. This is especially important given the contribution of animal sourced foods to nutrient adequacy in the global South and vulnerable populations of high-income countries (e.g., children, women of reproductive age and elderly). Often, however, LCAs simplify this reality by using 'protein' as a functional unit in their models and basing their analyses on generic nutritional requirements. Even if a 'nutritional functional unit' (nFU) is utilised, it is unlikely to consider the complexities of amino acid composition and subsequent protein accretion. The discussion herein focuses on nutritional LCA (nLCA), particularly on the usefulness of nFUs such as 'protein,' and whether protein quality should be considered when adopting the nutrient as an (n)FU. Further, a novel and informative case study is provided to demonstrate the strengths and weaknesses of protein-quality adjustment., Case Study Methods: To complement current discussions, we present an exploratory virtual experiment to determine how Digestible Indispensable Amino Acid Scores (DIAAS) might play a role in nLCA development by correcting for amino acid quality and digestibility. DIAAS is a scoring mechanism which considers the limiting indispensable amino acids (IAAs) within an IAA balance of a given food (or meal) and provides a percentage contribution relative to recommended daily intakes for IAA and subsequent protein anabolism; for clarity, we focus only on single food items (4 × animal-based products and 4 × plant-based products) in the current case exemplar. Further, we take beef as a sensitivity analysis example (which we particularly recommend when considering IAA complementarity at the meal-level) to elucidate how various cuts of the same intermediary product could affect the interpretation of nLCA results of the end-product(s)., Recommendations: First, we provide a list of suggestions which are intended to (a) assist with deciding whether protein-quality correction is necessary for a specific research question and (b) acknowledge additional uncertainties by providing mitigating opportunities to avoid misinterpretation (or worse, dis-interpretation) of protein-focused nLCA studies. We conclude that as relevant (primary) data availability from supply chain 'gatekeepers' (e.g., international agri-food distributors and processors) becomes more prevalent, detailed consideration of IAA provision of contrasting protein sources needs to be acknowledged-ideally quantitatively with DIAAS being one example-in nLCA studies utilising protein as a nFU. We also contend that future nLCA studies should discuss the complementarity of amino acid balances at the meal-level, as a minimum, rather than the product level when assessing protein metabolic responses of consumers. Additionally, a broader set of nutrients should ideally be included when evaluating "protein-rich foods" which provide nutrients that extend beyond amino acids, which is of particular importance when exploring dietary-level nLCA., Competing Interests: Conflict of interestsG.A.M, A.L.C., T.T., M.R.F.L. S.J.M, J.L.B, F.O., T.H., J.C.v.d.P., and T.B. declare no known conflicts of interest which would affect their interpretation of the work reported herein. FL is a nonremunerated board member of various academic non-profit organisations including the Belgian Association for Meat Science and Technology (president), the Belgian Society for Food Microbiology (president), and the Belgian Nutrition Society. On a nonremunerated basis, he also has a seat in the scientific committee of the Institute Danone Belgium, the World Farmers’ Organization, the Advisory Commission for the “Protection of Geographical Denominations and Guaranteed Traditional Specialties for Agricultural Products and Foods” of the Ministry of the Brussels Capital Region. On a nonremunerated basis, FL, TB, and SvV are part of a Scientific Advisory Committee of the Food and Agriculture Organization of the United Nations., (© The Author(s) 2022.)

Team-sports staff often administer non-exhaustive exercise assessments with a view to evaluating physiological state, to inform decision making on athlete management (e.g., future training or recovery). Submaximal fitness tests have become prominent in team-sports settings for observing responses to a standardized physical stimulus, likely because of their time-efficient nature, relative ease of administration, and physiological rationale. It is evident, however, that many variations of submaximal fitness test characteristics, response measures, and monitoring purposes exist. The aim of this scoping review is to provide a theoretical framework of submaximal fitness tests and a detailed summary of their use as proxy indicators of training effects in team sports. Using a review of the literature stemming from a systematic search strategy, we identified five distinct submaximal fitness test protocols characterized in their combinations of exercise regimen (continuous or intermittent) and the progression of exercise intensity (fixed, incremental, or variable). Heart rate-derived indices were the most studied outcome measures in submaximal fitness tests and included exercise (exercise heart rate) and recovery (heart rate recovery and vagal-related heart rate variability) responses. Despite the disparity between studies, these measures appear more relevant to detect positive chronic endurance-oriented training effects, whereas their role in detecting negative transient effects associated with variations in autonomic nervous system function is not yet clear. Subjective outcome measures such as ratings of perceived exertion were less common in team sports, but their potential utility when collected alongside objective measures (e.g., exercise heart rate) has been advocated. Mechanical outcome measures either included global positioning system-derived locomotor outputs such as distance covered, primarily during standardized training drills (e.g., small-sided games) to monitor exercise performance, or responses derived from inertial measurement units to make inferences about lower limb neuromuscular function. Whilst there is an emerging interest regarding the utility of these mechanical measures, their measurement properties and underpinning mechanisms are yet to be fully established. Here, we provide a deeper synthesis of the available literature, culminating with evidence-based practical recommendations and directions for future research., (© 2022. The Author(s).)

Between 2014 and 2016, there were two severe community water system (CWS) failures in Flint, Michigan (MI), USA and Havelock North, Hawkes Bay, New Zealand. These events had profound implications for public health in their respective countries. While the nature of both crises was different, certain aspects of the failings were strikingly similar. These included: failure of authorities to protect the integrity of their source water, 'wait-and-see approach' to address problems if and when they occurred, negligent approach to regulatory oversight and responsibility, substandard facilities and lack of knowledge and training of staff, failure of consultants and advisory services engaged by suppliers, and failure of government agencies to enforce regulations. The lessons from both incidents must be learned, or similar tragic events are likely to reoccur. The six principles identified in the Government Inquiry into the Havelock North outbreak are an essential first step. The next step is to implement them throughout the drinking water sector.

Purpose: To examine the utility of differential ratings of perceived exertion (dRPE) for monitoring internal intensity and load in association football., Methods: Data were collected from 2 elite senior male football teams during 1 season (N = 55). External intensity and load data (duration × intensity) were collected during each training and match session using electronic performance and tracking systems. After each session, players rated their perceived breathlessness and leg-muscle exertion. Descriptive statistics were calculated to quantify how often players rated the 2 types of rating of perceived exertion differently (dRPEDIFF). In addition, the association between dRPEDIFF and external intensity and load was examined. First, the associations between single external variables and dRPEDIFF were analyzed using a mixed-effects logistic regression model. Second, the link between dRPEDIFF and session types with distinctive external profiles was examined using the Pearson chi-square test of independence., Results: On average, players rated their session perceived breathlessness and leg-muscle exertion differently in 22% of the sessions (range: 0%-64%). Confidence limits for the effect of single external variables on dRPEDIFF spanned across largely positive and negative values for all variables, indicating no conclusive findings. The analysis based on session type indicated that players differentiated more often in matches and intense training sessions, but there was no pattern in the direction of differentiation., Conclusions: The findings of this study provide no evidence supporting the utility of dRPE for monitoring internal intensity and load in football.

A recent paper called for the abandonment of the term load (and training load) when used outside its mechanical meaning, claiming it is "unscientific" and "breaches scientific principles." In this article, we explain why its use does not breach any scientific principles and we clarify the process of labelling, conceptualising and operationalising a construct. Training load is simply a label attributed to a higher-order construct overarching other interrelated sub-dimensions. This multi-level structure provides a framework (nomological network) to support the research process and also practical applications. Load is a word, and therefore cannot be "unscientific". The "use" or "misuse" of words and terms entirely depends upon definitions that should be based on current understanding. Misuse occurs when a term is decontextualised or interpreted according to a unilateral perspective. The field of mechanics does not have a monopoly on the term load (or other common terms such as work, stress and fatigue), which are legitimately used in many scientific areas and with various meanings. The 'obligation' to rely on terms abiding by the Système International d'Unités (SI) when describing a construct is inappropriate. The SI relates to how we can measure, not describe training load; i.e., SI is relevant to its operational and not its constitutive (descriptive) definition. Discussions regarding shared and standardised descriptions and definitions are more relevant than discussions about discarding terms in sport and exercise science. Researchers (and practitioners) can continue to use the term training load as it does not breach any scientific principles., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

We aimed to examine the reliability, validity and sensitivity of an individualised sub-maximal fitness test (SMFTIFT60). Nineteen elite rugby league players performed a one-week test-retest of SMFTIFT60. Typical Errors and ICCs were: small (<3.5%) and extremely high (>0.90) for accelerometer-derived variables; moderate (<2.5% points) and moderate to very high (0.71-0.89) for exercise and recovery heart rate (HRex and HRR, respectively). Convergent validity correlations with the 10-week pre-season change in 30-15 Intermittent Fitness Test performance were large for changes in SMFTIFT60 HRex (r = -0.57) and HRR (0.60), and very large for changes in accelerometer measures (range: -0.71 to -0.79). For sensitivity, within-player dose-response relationships between SMFTIFT60 HRex and prior 3-day training loads were negative and ranged from moderate (session ratings of perceived exertion [sRPE-TL], r = -0.34), to large (high-speed running distance, -0.51; acceleration load, -0.73) and very large (heart rate Training Impulse [TRIMP], -0.83). All other relationships were unclear or trivial to small. Physiological and accelerometer-derived measures from the SMFTIFT60 are reliable and valid for the assessment of fitness in rugby league players. Only HRex appears sensitive to acute changes in training load. The SMFTIFT60 could be a useful monitoring tool in team sports.

Horizontal jumps are discrete, fast, over-ground movements requiring coordination of the centre of mass (CoM) and base of support and are routinely assessed in sports settings. There is currently no biomechanics-based system to aid in their quick and objective large-scale assessment. We describe a practical system combining a single low-cost depth-sensing camera and point-cloud processing (PCP) to capture whole-body CoM and foot kinematics. Fourteen participants performed 10 single-leg horizontal jumps for distance. Foot displacement, CoM displacement, CoM peak velocity and CoM peak acceleration in the anterior-posterior direction of movement were compared with a reference 15-segment criterion model, captured concurrently using a nine-camera motion capture system (Vicon Motion Systems, UK). Between-system Pearson's correlations were very-large to near-perfect (n = 140; foot displacement = 0.99, CoM displacement = 0.98, CoM peak velocity = 0.97, CoM peak acceleration = 0.79), with mean biases being trivial-small (-0.07 cm [0.12%], 3.8 cm [3.5%], 0.03 m·s -1 [1.6%], 0.42 m·s -2 [7%], respectively) and typical errors being trivial-small for displacement (foot: 0.92 cm [0.8%]; CoM: 3.8 cm [3.4%]) and CoM peak velocity (0.07 m·s -1 [4.3%]), and large for CoM peak acceleration (0.72 m·s -2 [15%]). Limits of agreement were -1.9 to 2.0 cm for foot displacement, -11.3 to 3.6 cm for CoM displacement, -0.17 to 0.12 m·s -1 for CoM peak velocity and -2.28 to 1.43 m·s -2 for CoM peak acceleration. The practical system captured CoM and foot kinematics during horizontal jumps with acceptable precision. Further work to improve estimates of CoM accelerations and different populations are warranted., (Crown Copyright © 2022. Published by Elsevier Ltd. All rights reserved.)