Development of a Revised Conceptual Framework of Physical Training for Use in Research and Practice

A Review of the Validity and Reliability of Accelerometer-Based Metrics From Upper Back-Mounted GNSS Player Tracking Systems for Athlete Training Load Monitoring

ABSTRACT

Dawson, L, Beato, M, Devereux, G, and McErlain-Naylor, SA. A review of the validity and reliability of accelerometer-based metrics from upper back-mounted GNSS player tracking systems for athlete training load monitoring. J Strength Cond Res 38(8): e460-e475, 2024-Athlete load monitoring using upper back-mounted global navigation satellite system (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. Because there are currently no feasible gold standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoad, Dynamic Stress Load, Body Load) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes because of mass or technique differences or between manufacturers because of processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.

Using Bar Velocity to Assess Post-match Neuromuscular Fatigue in Young Soccer Players

This study aimed to investigate the recovery of neuromuscular performance using mechanical parameters collected during jump (vertical and horizontal) and strength-power exercises in youth soccer players after official soccer matches. Twenty-one outfield highly trained youth male soccer athletes (age: 18.23±0.73 years; weight: 72.12±6.99 kg; height: 1.78±0.08 m) from two teams competing in the 1st division of U-19 Portuguese National Championship participated in this study. Players completed a battery of physical tests at -2 h, + 30 min, +24 h, and +48 h in relation to the match. Countermovement jump height, horizontal jump distance, and bar velocity during the half squat, bench press, and hip thrust exercises, at fixed loads, were recorded. Countermovement jump was impaired until 24 h post-match (-: 1.7% from pre- to 24 h post-match, p=0.050; ES=-: 0.82). Half-squat bar velocity was reduced immediately following the match (-: 6.8% from pre-match, p=0.004; ES=-: 0.64) but recovered at +24 h (+2.9%, p=1.00; ES=0.02). Hip-thrust bar velocity was reduced for up to 48 h post-match (-: 7.4% from pre- to 48 h post-match, p<0.001; ES=-: 0.80). No impairments were found in the horizontal jump and bench press at any moment. Our findings show prolonged decrements in strength of the posterior chain following a soccer match, measured in the hip thrust exercise, while the other exercises displayed faster recovery dynamics.

Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review

BACKGROUND

Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.

OBJECTIVES

The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).

METHODS

PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.

RESULTS

Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s-2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s-1) and acceleration/deceleration zones (> 2.0 m·s-2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.

CONCLUSIONS

Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.

Relationship Between External Training Load and Session Rating of Perceived Exertion Training Impulse in Elite Sprinters

PURPOSE

To quantify the change in session rating of perceived exertion training impulse (RPE-TRIMP) that may occur in response to increased running distance at 3 running velocity ranges in elite sprinters.

METHODS

We monitored training load in elite sprinters (women: n = 7; men: n = 11) using wearable Global Positioning System technology and RPE-TRIMP for a total of 681 individual training sessions during a 22-week competition-preparation period. Internal training load was operationalized by RPE-TRIMP, and external training load was operationalized by distance covered in 3 velocity ranges. A linear mixed-effects model with athlete as a random effect was fit to RPE-TRIMP with total distance covered at ≤69.99% (low-velocity running [LVR]), 70% to 84.99% (high-velocity running [HVR]), and 85% to 100% (very-high-velocity running [VHVR]) of individual maximum velocity.

RESULTS

Increased running distance in all 3 velocity ranges (LVR, HVR, and VHVR) resulted in a significant (P < .001) increase in RPE-TRIMP. Coefficients (95% CIs) were .10 (.08-.11) for LVR, .23 (.18-.28) for HVR, and .44 (.35-.53) for VHVR. A 50-m increase in running distance covered in the LVR, HVR, and VHVR velocity ranges was associated with increases in RPE-TRIMP of 5, 11.5, and 22 arbitrary units, respectively.

CONCLUSIONS

Internal training load, calculated as RPE-TRIMP, increased with increases in total distance covered in the LVR, HVR, and VHVR velocity ranges (P < .001). RPE-TRIMP can be a practical solution for monitoring global training-session load in elite sprinters.

A Biopsychosocial Model for Understanding Training Load, Fatigue, and Musculoskeletal Sport Injury in University Athletes: A Scoping Review

ABSTRACT

McClean, ZJ, Pasanen, K, Lun, V, Charest, J, Herzog, W, Werthner, P, Black, A, Vleuten, RV, Lacoste, E, and Jordan, MJ. A biopsychosocial model for understanding training load, fatigue, and musculoskeletal sport injury in university athletes: A scoping review. J Strength Cond Res 38(6): 1177-1188, 2024-The impact of musculoskeletal (MSK) injury on athlete health and performance has been studied extensively in youth sport and elite sport. Current research examining the relationship between training load, injury, and fatigue in university athletes is sparse. Furthermore, a range of contextual factors that influence the training load-fatigue-injury relationship exist, necessitating an integrative biopsychosocial model to address primary and secondary injury prevention research. The objectives of this review were (a) to review the scientific literature examining the relationship between training load, fatigue, and MSK injury in university athletes and (b) to use this review in conjunction with a transdisciplinary research team to identify biopsychosocial factors that influence MSK injury and develop an updated, holistic biopsychosocial model to inform injury prevention research and practice in university sport. Ten articles were identified for inclusion in this review. Key findings were an absence of injury surveillance methodology and contextual factors that can influence the training load-fatigue-MSK injury relationship. We highlight the inclusion of academic load, social load, and mental health load as key variables contributing to a multifactorial, gendered environmental, scientific inquiry on sport injury and reinjury in university sport. An integrative biopsychosocial model for MSK injury in university sport is presented that can be used to study the biological, psychological, and social factors that modulate injury and reinjury risk in university athletes. Finally, we provide an example of how causal inference can be used to maximize the utility of longitudinally collected observational data that is characteristic of sport performance research in university sport.

Effect of Level of Competition and Drill Typology on Internal and External Load in Male Volleyball Players During the Preseason Period

PURPOSE

This study aimed at evaluating the effect of level of competition and drill typology on loads during the preseason period in male volleyball players.

METHODS

Internal (percentage of peak heart rate [HR] and summated HR zone) and external (PlayerLoad per minute, total and high accelerations per minute [tACCmin and hACCmin], decelerations per minute [tDECmin and hDECmin], and jumps per minute [tJUMPmin and hJUMPmin]) loads were monitored across a 5-week preseason period in 12 Division 1 (age: 22.5 [3.9] y; stature: 188 [6.2] cm; body mass: 85 [11.6] kg; training experience: 9.4 [4.2] y) and 12 Division 2 (age: 20.7 [2.9] y; stature: 186 [6.2] cm; body mass: 77.8 [9.6] kg; training experience: 5.6 [2.3] y) male volleyball players. Furthermore, differences in load were assessed for each drill typology (warm-up, conditioning, technical, tactical, and integral).

RESULTS

No effects (P > .05) of level of competition on the internal (except for summated HR zone, P = .05) and external loads (except for tJUMPmin, P = .002) were found. Differently, drill typologies showed an effect (P < .001) on all the investigated internal- and external-load measures. The main post hoc results revealed higher (P < .05) percentage of peak HR, summated HR zone, PlayerLoad per minute, and tACCmin in warm-up and conditioning drills, while higher (P < .05) hDECmin and hJUMPmin were found in tactical and integral drills.

CONCLUSIONS

These results suggest that volleyball coaches use warm-up and conditioning drills when aiming at increasing the internal loads, PlayerLoad per minute, and tACCmin, while tactical and integral drills should be preferred to enhance the number of hDECmin and hJUMPmin.

Monitoring Readiness to Train and Perform in Female Football: Current Evidence and Recommendations for Practitioners

PURPOSE

Monitoring player readiness to train and perform is an important practical concept in football. Despite an abundance of research in this area in the male game, to date, research is limited in female football. The aims of this study were, first, to summarize the current literature on the monitoring of readiness in female football; second, to summarize the current evidence regarding the monitoring of the menstrual cycle and its potential impact on physical preparation and performance in female footballers; and third, to offer practical recommendations based on the current evidence for practitioners working with female football players.

CONCLUSIONS

Practitioners should include both objective (eg, heart rate and countermovement jump) and subjective measures (eg, athlete-reported outcome measures) in their monitoring practices. This would allow them to have a better picture of female players' readiness. Practitioners should assess the reliability of their monitoring (objective and subjective) tools before adopting them with their players. The use of athlete-reported outcome measures could play a key role in contexts where technology is not available (eg, in semiprofessional and amateur clubs); however, practitioners need to be aware that many single-item athlete-reported outcome measures instruments have not been properly validated. Finally, tracking the menstrual cycle can identify menstrual dysfunction (eg, infrequent or irregular menstruation) that can indicate a state of low energy availability or an underlying gynecological issue, both of which warrant further investigation by medical practitioners.

External Load Fluctuations Across an Amateur Athletic Union Basketball Season

ABSTRACT

Kutson, CW, Russell, JL, Strack, D, Coutts, AJ, and McLean, BD. External load fluctuations across an Amateur Athletic Union basketball season. J Strength Cond Res 38(3): 592-598, 2024-Amateur Athletic Union (AAU) competitions are an important component of the developmental pathway for youth basketball athletes. Despite its relative importance, there is currently a paucity of research investigating the physical demands in AAU basketball. Therefore, the purpose of this study was to examine the physical demands encountered over the course of an AAU basketball season. External training load was quantified using inertial sensors (Catapult T6) from one male AAU basketball team (age: 17.5 ± 0.5 years, height: 197.3 ± 10.0 cm, and mass: 89.4 ± 11.6 kg) over the course of the 2021 AAU season and categorized post hoc into high-, medium-, and low-minute groups based on mean playing minutes. After player categorization, 2 linear mixed models were constructed, one for PlayerLoad (PL) and one for duration, to examine the differences across player category, month of the season, and activity types (practices or games). The results show that the highest training loads were encountered by high-minute players, who had total PLs of 9,766 ± 1,516 AU, 13,207 ± 2,561 AU, and 7,071 ± 2,122 AU during April, May, and June, respectively. Highly variable training loads were also evident over the course of a season, with peak PL values as high as 4,921 AU per week. Practitioners should be aware that AAU basketball players experience variable loads throughout the season, which peak around congested competition/tournament periods. In addition, players with high game minutes accumulate the most load over the course of a season. This information may be used to better inform planning and periodizing strategies during developmental phases.

ChatGPT Generated Training Plans for Runners are not Rated Optimal by Coaching Experts, but Increase in Quality with Additional Input Information

ChatGPT may be used by runners to generate training plans to enhance performance or health aspects. However, the quality of ChatGPT generated training plans based on different input information is unknown. The objective of the study was to evaluate ChatGPT-generated six-week training plans for runners based on different input information granularity. Three training plans were generated by ChatGPT using different input information granularity. 22 quality criteria for training plans were drawn from the literature and used to evaluate training plans by coaching experts on a 1-5 Likert Scale. A Friedmann test assessed significant differences in quality between training plans. For training plans 1, 2 and 3, a median rating of <3 was given 19, 11, and 1 times, a median rating of 3 was given 3, 5, and 8 times and a median rating of >3 was given 0, 6, 13 times, respectively. Training plan 1 received significantly lower ratings compared to training plan 2 for 3 criteria, and 15 times significantly lower ratings compared to training plan 3 (p < 0.05). Training plan 2 received significantly lower ratings (p < 0.05) compared to plan 3 for 9 criteria. ChatGPT generated plans are ranked sub-optimally by coaching experts, although the quality increases when more input information are provided. An understanding of aspects relevant to programming distance running training is important, and we advise avoiding the use of ChatGPT generated training plans without an expert coach's feedback.

The Relationships Between External and Internal Training Loads in Mixed Martial Arts

PURPOSE

As a multidisciplined combat sport, relationships between external and internal training loads and intensities of mixed martial arts (MMA) have not been described. The aim of this study was to determine the external loads and intensities of MMA training categories and their relationship to internal loads and intensities.

METHODS

Twenty MMA athletes (age = 23.3 [5.3] y, mass = 72.1 [7.2] kg, stature = 171.5 [8.4] cm) were observed for 2 consecutive weeks. Internal load and intensity (session rating of perceived exertion [sRPE]) were calculated using the Foster RPE for the session overall (sRPE-training load [TL]) and segmented RPE (segRPE-TL) for each training category: warm-up, striking drills, wrestling drills, Brazilian jiujitsu (BJJ) drills, striking sparring, wrestling sparring, BJJ sparring, and MMA sparring. External load and intensity were measured via Catapult OptimEye S5 for the full duration of each session using accumulated Playerload (PLdACC) and PLdACC per minute (PLdACC·min-1). Differences in loads between categories and days were assessed via Bayesian analysis of variance (BF10 ≥ 3). Predictive relationships between internal and external variables were calculated using Bayesian regression.

RESULTS

Session overall sRPE-TL = 448.6 (191.1) arbitrary units (AU); PLdACC = 310.6 (112) AU. Category segRPE-TL range = 33.8 (22.6) AU (warm-up) to 122.8 (54.6) AU (BJJ drills). Category PLdACC range = 44 (36.3) AU (warm-up) to 125 (58.8) AU (MMA sparring). Neither sRPE-TL nor PLdACC changed between days. PLdACC was different between categories. Evidence for regressions was strong-decisive except for BJJ drills (BF10 = 7, moderate). R2 range = .50 to .77, except for warm-up (R2 = .17), BJJ drills (R2 = .27), BJJ sparring (R2 = .49), and session overall (R2 = .13).

CONCLUSIONS

While MMA training categories may be differentiated in terms of external load, overall session external load does not change within or between weeks. Resultant regression equations may be used to appropriately plan MMA technical/tactical training loads.

Weekly Fluctuations in, and Associations Between, Salivary Hormone Responses, Load, and Well-Being During the Pre-season in Professional Male Basketball Players

ABSTRACT

Kamarauskas, P, Scanlan, A, Ferioli, D, and Conte, D. Weekly fluctuations in, and associations between, salivary hormone responses, load, and well-being during the pre-season in professional male basketball players. J Strength Cond Res 38(1): 128-135, 2024-This study aimed to (a) quantify weekly fluctuations in hormonal responses (testosterone [T], cortisol [C], and their ratio [T:C]), external (PlayerLoad [PL] and PL·minute-1) and internal (session rating of perceived exertion load [sRPE-load], summated heart rate zones [SHRZs], and percentage of maximal heart rate [%HRmax]) load measures, and well-being measured using a self-reported questionnaire and (b) determine the associations between weekly changes in hormonal responses and load measures with weekly changes in well-being during the pre-season phase in basketball players. Twenty-one professional male basketball players (age: 26.2 ± 4.9 years) were monitored during a 5-week pre-season phase. Linear mixed models were used to determine weekly differences in each variable and associations between weekly changes in hormonal and load variables with weekly changes in well-being. Findings revealed that T (p < 0.001) and T:C (p = 0.002) increased toward the end of the pre-season phase. Moreover, higher (p < 0.05) external (PL·minute-1) and internal (%HRmax) load intensities were evident during the first 3 weeks of the pre-season, with no significant fluctuations in other load variables. Weekly changes in PL and sRPE-load were negatively associated (p < 0.05) with weekly changes in well-being, albeit weak in magnitudes (R2 = 0.061-0.105). These results highlight that a periodized approach was undertaken across the pre-season predominantly predicated on altering weekly load intensities, which coincided with positive hormonal responses toward the end of the pre-season. In addition, weak relationships were evident between weekly changes in hormonal responses and load measures with well-being, emphasizing that a low commonality may be present between these constructs.

The Relationship Between Isometric and Dynamic Strength Following Resistance Training: A Systematic Review, Meta-Analysis, and Level of Agreement

BACKGROUND

Maximal lower-body strength can be assessed both dynamically and isometrically; however, the relationship between the changes in these 2 forms of strength following resistance training is not well understood.

PURPOSE

To systematically review and analyze the effects of resistance training on changes in maximal dynamic (1-repetition-maximum back squat, deadlift, and power clean) and position-matched isometric strength (isometric midthigh pull and the isometric squat). In addition, individual-level data were used to quantify the agreement and relationship between changes in dynamic and isometric strength.

METHODS

Databases were systematically searched to identify eligible articles, and meta-analysis procedures were performed on the extracted data. The raw results from 4 studies were acquired, enabling bias and absolute reliability measures to be calculated using Bland-Altman test of agreement.

RESULTS

Eleven studies met the inclusion criteria, which resulted in 29 isometric-dynamic change comparisons. The overall pooled effect was 0.13 in favor of dynamic testing; however, the prediction interval ranged from g = -0.49 to 0.75. There was no evidence of bias (P = .825) between isometric and dynamic tests; however, the reliability coefficient was estimated to be 16%, and the coefficient of variation (%) was 109.27.

CONCLUSIONS

As a range of future effects can be expected when comparing isometric to dynamic strength changes following resistance training, and limited proportionality exists between changes in these 2 strength qualities, there is strong evidence that isometric and dynamic strength represent separate neuromuscular domains. These findings can be used to inform strength-assessment models in athlete populations.

The Effects of Low-Load Squat Jump and Maximal Isometric Priming Exercise on Muscular Performance and Perceptual State

ABSTRACT

Harrison, PW, James, LP, Jenkins, DG, McGuigan, MR, Holmberg, PM, and Kelly, VG. The effects of low-load squat jump and maximal isometric priming exercise on muscular performance and perceptual state. J Strength Cond Res 38(1): 1-9, 2024-The aim of this study was to examine responses at 3 and 27 hours after low-load jump squat (LL) and maximal isometric half-squat (ISO) priming stimuli. Fifteen resistance-trained males performed LL (4 × 3 at 20% 1 repetition maximum [1RM]), ISO (4 × 3 seconds), and control (CON) activities (standardized warm-up) in a randomized and counterbalanced order. Countermovement jump (CMJ) and isometric midthigh pull tests were conducted to assess performance changes after priming and CON activities. No clear changes in CMJ measures were found after priming activities compared with CON. However, small effect size improvements were found after priming stimuli completed on the same day. A 2.9% decrease in concentric phase duration (CI = 0.3-5.9, p = 0.333, Cliff's delta = -0.156) and a 9.1% increase in RSImod (CI = 0.2-12.3, p = 0.151, Cliff's delta = -0.218) occurred at 3 hours after LL compared with CON. Braking phase duration (CI = 0.8-10.6, p = 0.333, Cliff's delta = -0.213) was 2.9% shorter at 3 hours after ISO compared with CON. No clear changes in isometric peak force occurred after priming activities compared with CON. Additionally, questionnaires were completed to assess perceptual state and perceived effectiveness of the priming stimulus to influence performance. An increase in the "effect of activity" was perceived at 3 hours after LL and ISO (p = 0.013-0.044, Cliff's delta = 0.578-0.6) and at 27 hours after ISO (p = 0.99, Cliff's delta = 0.173) compared with CON. An increase in "muscular heaviness" was also reported at 3 hours after ISO compared with CON (p = 0.199, Cliff's delta = 0.320). The collective findings suggest limited benefits over the day after LL and ISO priming stimuli. However, as there was substantial variation in individual responses, the relative nature of priming responses should be considered when prescribing similar strategies in practical environments.

Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis

This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professional soccer players; (2) carried out for at least 2 sessions, exercises, or competitions; (3) correlated training load (TL) with non-contact injuries; (4) applied ML approaches to predict TL and non-contact injuries. TL included: IL indicators (Rating of Perceived Exertion, RPE; Session-RPE, Heart Rate, HR) and EL indicators (Global Positioning System, GPS variables); the relationship between EL and IL through index, ratio, formula; ML indicators included performance measures, predictive performance of ML methods, measure of feature importance, relevant predictors, outcome variable, predictor variable, data pre-processing, features selection, ML methods. Twenty-five studies were included. Eleven addressed the relationship between EL and IL. Five used EL/IL indexes. Five studies predicted IL indicators. Three studies investigated the association between EL and IL with IR. One study predicted IR using ML. Significant positive correlations were found between S-RPE and total distance (TD) (r = 0.73; 95% CI (0.64 to 0.82)) as well as between S-RPE and player load (PL) (r = 0.76; 95% CI (0.68 to 0.84)). Association between IL and EL and their relationship with injuries were found. RPE, S-RPE, and HR were associated with different EL indicators. A positive relationship between EL and IL indicators and IR was also observed. Moreover, new indexes or ratios (integrating EL and IL) to improve knowledge regarding TL and fitness status were also applied. ML can predict IL indicators (HR and RPE), and IR. The present systematic review was registered in PROSPERO (CRD42021245312).

Female basketball game performance is influenced by menstrual cycle phase, age, perceived demands and game-related contextual factors

This study evaluated the influence of physical and perceived game demands, menstrual cycle phase, perceived recovery, individual and game-related contextual factors on competitive performance in professional, female basketball players.11 professional female players (age: 20.6 ± 2.7 years) were monitored for game-related statistics (Performance Index Rating, PIR; rebounds, REB; effective field goal %, eFG%; turnovers, TO), objective (PlayerLoad per minute, PL·min-1) and subjective (RPE) game loads, pre-game perceived recovery (Total Quality Recovery, TQRpre), menstrual phase (follicular; luteal) and game-related contextual factors (game location; game outcome; score differential; opponent level) during 12 official games. Separate linear mixed models were used to evaluate the influence of RPE, PL·min-1, TQRpre, menstrual phase, contextual factors, and individual characteristics (age; playing position) on game-related statistics.Higher PIR and eFG% were found for older players and those who reported higher RPE (all p < 0.05). Higher age also led to less TO (p = 0.042). eFG% was higher when players reported higher TQRpre ;(p = 0.010). Better shooting (eFG%) and rebounding (REB) performances were found during the follicular menstrual phase (p < 0.05). More REB were collected in won games (p = 0.002).This study suggests that the co-influences of perceptual, menstrual-related, individual and game-related contextual factors should be considered to optimise female basketball players' performance.

Understanding Training Load as Exposure and Dose

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.

Toward a New Conceptual Approach to "Intensity" in Soccer Player's Monitoring: A Narrative Review

ABSTRACT

Pillitteri, G, Clemente, FM, Petrucci, M, Rossi, A, Bellafiore, M, Bianco, A, Palma, A, and Battaglia, G. Toward a new conceptual approach to "intensity" in soccer player's monitoring: A narrative review. J Strength Cond Res 37(9): 1896-1911, 2023-In the last decade, monitoring physiological and match-related demands in soccer has become an increasingly common practice in sports sciences. One of the great challenges during monitoring process is the identification of key indicators that permit to generalize evidence and sustain decision-making process during training prescription. Actually, one of the major debates in the scientific community and among practitioners is the identification of the "intensity" concept. Defining a given training session or exercise based on "intensity" is difficult due to the fact that a huge amount of indicators are available (related both to the performed activities and to the athletes' psychophysiological responses). These indicators can lead to specific outcomes with different interpretations. The current narrative review aims to discuss the different measures approaches used in soccer to describe the intensity for both internal and external demands. In addition, a second purpose of this review is to propose general recommendations for combining intensity indicators with the aim of defining an overall intensity score of a training session or drill.

Concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit to measure velocity during team sport activity

The concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit (F-IMU) was investigated during linear and change of direction running drills. Sixteen individuals performed four repetitions of two drills (maximal acceleration and flying 10 m sprint) and five repetitions of a multi-directional movement protocol. Participants wore two F-IMUs (Playermaker) and 10 retro-reflective markers to allow for comparisons to the criterion system (Qualisys). Validity of the F-IMU derived velocity was assessed via root-mean-square error (RMSE), 95% limits of agreement (LoA) and mean difference with 95% confidence interval (CI). Between-unit reliability was assessed via intraclass correlation (ICC) with 90% CI and 95% LoA. The mean difference for instantaneous velocity for all participants and drills combined was -0.048 ± 0.581 m ∙ s^-1, the LoA were from -1.09 to -1.186 m ∙ s^-1 and RMSE was 0.583 m ∙ s^-1. The ICC ranged from 0.84 to 1, with LoA from -7.412 to 2.924 m ∙ s^-1. Differences were dependent on the reference speed, with the greatest absolute difference (-0.66 m ∙ s^-1) found at velocities above 7 m ∙ s^-1. Between-unit reliability of the F-IMU ranges from good to excellent for all locomotor characteristics. Playermaker has good agreement with 3D motion capture for velocity and good to excellent between-unit reliability.

Case study of IMU loads and self-reported fatigue monitoring of water polo goalkeepers preparing for the Olympic games

Introduction

Measurement of training in water polo goalkeepers has focused first on psycho-physiological variables, but also on external volume estimated with wearable sensors. However, there are limited studies exploring training monitoring in water polo goalkeepers longitudinally.

Methods

Three female senior national team goalkeepers participated in this study from May to August 2021. Internal loads were defined using session rating of perceived exertion (sRPE). Tri-axial accelerations and angular velocities were measured with an inertial measurement unit (IMU) placed on the lower back to measure external loads. Relationships between self-reported and IMU-derived metrics were explored using Spearman correlations. Two-way ANOVAs were used to assess differences between session types and between athletes.

Results

In total, 247 sessions were collected (159 practices, 67 matches and 21 game warm up), with 155 sessions having complete data. IMU metrics, such as number of kicks, number of jumps or player-load showed high correlation with each other (ρ = 0.80-0.88). There was also a moderate correlation (ρ = 0.47, 95% CI = 0.33-0.58) between sRPE and player-load measured with the IMU. ANOVA tests showed that there were significant differences between athletes for sRPE (p < 0.01) but not for player load (p = 0.47). There were no interactions between athletes and training types, except for index score (p < 0.01).

Conclusions

This study shows that monitoring of training loads can be performed successfully in water polo goalkeepers using a combination of self-reported and IMU measures. Self-reported outcomes can be expected to vary significantly across athletes within the same session, while IMU metrics vary across training situations. Finally, coaches should be mindful of missing data, as they can skew the interpretation of training loads.

The Road to Becoming a World Champion in Futsal

PURPOSE

The aim of the current study was to report the training program and monitoring outcomes of the Portuguese national futsal team during the preparation and competition phases of the FIFA Futsal World Cup Lithuania 2021™. For that, the variations in training load and wellness were measured, as well as their relationship.

METHODS

The study followed a retrospective cohort design. For all field training sessions, the volume, exercise structure, and area of play were identified. Player load, session rating of perceived exertion (sRPE), and wellness were collected. Descriptive statistics and Kruskal-Wallis tests were used for comparison purposes. A visualization method was used for load and well-being.

RESULTS

No significant differences were observed in the number of training sessions, session duration, and player load between preparation and competitive periods. sRPE showed significantly higher values in preparation than in competition periods (P < .05, d = 0.86) and significant differences between weeks (P < .05, d = 1.08). Wellness showed a general statistical difference between periods (P < .001, d = 1.28) and weeks (P < .05, d = 1.17). The correlation analysis for the overall period revealed a general linear relationship within variables of training load and wellness (P < .001). Variations occurred for preparation and competition periods. The visualization method through quadrant plots allowed us to understand the adaptation of the team and the players over the specific period under analysis.

CONCLUSIONS

Through this study, it was possible to better understand the training program and monitoring strategies of a high-performance futsal team over a high-level tournament.

Association between internal load responses and recovery ability in U19 professional soccer players: A machine learning approach

Background

The objective of soccer training load (TL) is enhancing players' performance while minimizing the possible negative effects induced by fatigue. In this regard, monitoring workloads and recovery is necessary to avoid overload and injuries. Given the controversial results found in literature, this study aims to better understand the complex relationship between internal training load (IL) by using rating of perceived exertion (RPE), recovery, and availability (i.e., subjective players' readiness status).

Methods

In this cross-sectional study, twenty-two-professional soccer players (age: 18.5 ± 0.4 years, height: 177 ± 6 cm, weight: 67 ± 6.7 kg) competing in the U19 Italian Championship were monitored using RPE scale to assess IL, and TreS scale to detect information about recovery and training/match availability during an entire season (2021-2022).

Results

Autocorrelation analysis showed a repeated pattern with 7 days lag (weekly microcycle pattern) for all the variables considered (i.e., TL, recovery, and availability). For recovery (r = 0.64, p < 0.001) and availability (r = 0.63, p < 0.001) the best lag for both of them is 1 day. It indicates that recovery and availability are related to the past day value. Moreover, TL was found to be negatively affected by recovery and availability of the current day (lag = 0 day). Cross-correlation analysis indicates that TL is negatively affected by recovery (r = 0.46, p < 0.001) and availability (r = 0.42, p < 0.001) of the current day (lag = 0 day). In particular, lower recovery and availability will result in following lower TL. Furthermore, we found that TL negatively affects recovery (r = 0.52, p < 0.001) and availability (r = 0.39, p < 0.01) of the next day (lag = 1 day). In fact, the higher the TL in a current day is, the lower the recovery and availability in the next day will be.

Conclusion

In conclusion, this study highlights that there is a relationship between TL and recovery and that these components influence each other both on the same day and on the next one. The use of RPE and TreS scale to evaluate TL and recovery/availability of players allows practitioners to better adjust and schedule training within the microcycle to enhance performance while reducing injury risk.

Submaximal Fitness Test in Team Sports: A Systematic Review and Meta-Analysis of Exercise Heart Rate Measurement Properties

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 .

Intraindividual Relationships Between Training Loads and Heart-Rate Variability in High-Level Female Futsal Players: A Longitudinal Study

PURPOSE

To investigate the internal training loads of a professional Spanish female futsal team throughout 26 weeks of training including preseason and in-season weeks and verify the impact of training period and/or training load magnitudes on heart-rate variability responses. Furthermore, we aimed to assess, intraindividually, the relationship between training load and the coefficient of variation (CV) of weekly natural log of the root mean square difference of successive normal interbeat (RR) intervals (lnRMSSDCV), obtained from ∼5 measures per week, and recorded in the seated position.

METHODS

A within-subject design involved 12 high-level outfield female futsal players (mean [SD] age: 23.9 [3.4] y).

RESULTS

lnRMSSD was significantly lower and lnRMSSDCV was significantly higher during the preseason (weeks 1-6) compared to in-season (weeks 7-26) (P < .001). Individually, players presented moderate to large negative correlations between lnRMSSDCV and lnRMSSD during the 26 weeks of observation. Correlations ranged between rplayer4 = -.41 (95% CI, -.69 to -.02) and rplayer12 = -.55 (-.78 to -.18). Players also presented moderate to very large positive correlations between lnRMSSDCV and session rating of perceived exertion. Correlations ranged between rplayer7 = .41 (.04 to .71) and rplayer1 = .71 (.45 to .86).

CONCLUSION

Professional female futsal players in this study presented increased lnRMSSD and reduced lnRMSSDCV during 20 weeks into the competitive season compared to 6 weeks of preseason. Furthermore, lnRMSSDCV was negatively associated with lnRMSSD on an intraindividual basis. Finally, higher internal training loads were positively correlated with lnRMSSDCV, indicating that heart-rate variability is responsive to weekly training loads.

Performance Adaptations to Intensified Training in Top-Level Football

Because physical demands are surging in football (soccer, USA), clubs are more and more seeking players who have a high capacity to perform repeated intense exercise. High-intensity interval training (HIIT), comprising exercise performed at intensities near or exceeding the capacity of aerobic energy systems, effectively enhances the physical conditioning of players. But given that HIIT imposes high loads, it increases the risk of overload-associated match performance decline and injury. This makes some coaches inclined to conduct HIIT in the weeks leading up to the season and during the season. Therefore, the challenge is how to optimize and dose HIIT during these phases, as they can be decisive. Studies have highlighted the utility of conducting periods of intensified training to overcome the risk of overload while at the same time enhancing performance. During intensified training periods of typically a few weeks, intensity is increased by enlarging the amount of HIIT, for example, aerobic high-intensity training or speed endurance training, while volume at low-to-moderate intensity is significantly reduced. The outcome depends on training composition and prescription-most notably, intensity and duration of bouts and recovery. When work intervals are prescribed for a few minutes at intensities > 90% heart rate max (i.e., aerobic high-intensity training), then beneficial adaptations pertaining to aerobic power and capacity are apparent. But when work intervals are conducted at much higher intensities, as all-out efforts or sprinting of typically 10- to 40-s duration with longer recovery periods (i.e., speed endurance training), beneficial adaptations pertaining to anaerobic energy systems, ion handling, and fatigue resilience are commonly observed. In this review, we discuss the utility of conducting intensified training periods to enhance performance in elite football players during the late preparation phase and competitive season.

Match Load Physical Demands in U-19 Professional Soccer Players Assessed by a Wearable Inertial Sensor

BACKGROUND

Wearable inertial sensors are poorly used in soccer to monitor external load (EL) indicators. However, these devices could be useful for improving sports performance and potentially reducing the risk of injury. The aim of this study was to investigate the EL indicators (i.e., cinematic, mechanical, and metabolic) differences between playing positions (i.e., central backs, external strikers, fullbacks, midfielders, and wide midfielder) during the first half time of four official matches (OMs).

METHODS

13 young professional soccer players (Under-19; age: 18.5 ± 0.4 years; height: 177 ± 6 cm; weight: 67 ± 4.8 kg) were monitored through a wearable inertial sensor (TalentPlayers TPDev, firmware version 1.3) during the season 2021-2022. Participants' EL indicators were recorded during the first half time of four OMs.

RESULTS

significant differences were detected in all the EL indicators between playing positions except for two of them (i.e., distance traveled in the various metabolic power zones (<10 w) and the number of direction changes to the right >30° and with speed >2 m). Pairwise comparisons showed differences in EL indicators between playing positions.

CONCLUSIONS

Young professional soccer players showed different loads and performances during OMs in relation to playing positions. Coaches should consider the different physical demands related to playing positions in order to design the most appropriate training program.

Personalizing Resistance Training Mitigates Neuromuscular and Perceived Fatigue: The Autoregulation Cluster Training Method

PURPOSE

To compare predetermined and autoregulated resistance training sessions on velocity loss and perceived fatigue.

METHODS

Twenty-six resistance-trained men completed 3 sessions including the back-squat and bench-press exercises matched for load (75% of 1-repetition maximum), volume (24 repetitions), and total rest (240 s). Sessions were randomly performed as traditional set (TRA), 3 sets of 8 repetitions with 120-second interset rests; cluster interset-rest redistribution (IRR), 6 clusters of 4 repetitions with 48-second between-clusters rests; and autoregulation cluster training (ACT), a personalized combination of clusters, repetitions per cluster, and between-clusters rest regulated on a velocity loss threshold. The comparative effects were evaluated on velocity loss outputs measured with a linear encoder and perceived fatigue responses reported using a single-item scale.

RESULTS

IRR and ACT induced less velocity loss than TRA (b = -2.09, P < .001). ACT also mitigated velocity loss more than IRR (b = -2.31, P < .001). The back squat resulted in greater velocity loss compared to the bench press (b = 1.83, P < .001). Perceived fatigue responses mirrored the pattern observed for the velocity loss outputs (IRR and ACT vs TRA: b = -0.64, P < .001; ACT vs IRR: b = -1.05, P < .001; back squat vs bench press: b = 0.46, P = .005).

CONCLUSIONS

IRR and ACT reduced neuromuscular and perceived fatigue, likely due to their cluster-set structures' embedding frequent windows of interset rest. However, the ACT was overall more effective, presumably given its personalized structure.

Development and Validation of Single Items for Fatigue and Recovery in Dancers

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.

Psychophysiological Responses to a Preseason Training Camp in High-Level Youth Soccer Players

PURPOSE

This study aimed to examine the responsiveness of commonly used measurement instruments to a short training camp by examining the time course of psychophysiological responses in high-level youth soccer players.

METHODS

Monitoring was carried out in 14 U15 male soccer players of 1 professional youth academy. Players provided data 3 days prior to (D - 3), during (D2-D4), and 1 (D + 1) and 4 days (D + 4) after the camp: 4 items for the Short Recovery and Stress Scale (SRSS), a countermovement jump (CMJ), and a submaximal run to assess exercise heart rate and heart-rate recovery. Training load during the camp followed an alternating low-high pattern, with lower training loads on D1 and D3 and higher training loads on D2 and D4.

RESULTS

Changes in SRSS physical performance capability, emotional balance, overall recovery, muscular stress, and overall stress were small to moderate on D3 and moderate to large on D + 1, while changes were trivial on D + 4. Some CMJ parameters related to the eccentric phase were slightly improved on D3, and these parameters were slightly impaired on D4. Changes in CMJ parameters were trivial on D + 1 and D + 4. After a moderate decrease in exercise heart rate on D3, there was a small decrease on D + 4 and a moderate increase in heart-rate recovery.

CONCLUSION

Measurement instruments such as the SRSS and submaximal runs can be used to monitor acute psychophysiological responses to load, while the CMJ may provide little insight during periods of intensified training load.

Fractal correlation properties of HRV as a noninvasive biomarker to assess the physiological status of triathletes during simulated warm-up sessions at low exercise intensity: a pilot study

BACKGROUND

The non-linear index alpha 1 of Detrended Fluctuation Analysis (DFA a1) of heart rate variability, has been shown to be a marker of fatigue during endurance exercise. This report aims to explore its ability to assess the physiological status as a surrogate metric for "readiness to train" while performing simulated warm-up sessions the day after two different exercise sessions.

METHODS

11 triathletes were recruited to determine the first ventilatory threshold (VT1) during a baseline assessment and to perform 10-min of cycling at 90% of VT1 (simulating a warm-up bout) before (PRE) and within 36 h after (POST) light and heavy running exercise. RR intervals were recorded for DFA a1 analysis along with neuromuscular testing to verify the effects of the performed exercise sessions. In addition to common statistical methods, magnitude-based inferences (MBI) were applied to assess the changes in true score and thus also the practical relevance of the magnitude.

RESULTS

Rating of perceived exertion for the heavy exercise session showed a significant higher rating as opposed to the light exercise session (p < 0.001, d = 0.89). In regard of MBIs, PRE versus POST comparisons revealed a significant reduced DFA a1 with large effect size after the heavy exercise session (p = 0.001, d = - 1.44) and a 99% chance that this negative change was clinically relevant.

CONCLUSIONS

Despite inter-individual differences, DFA a1 offers potential to assess physiological status and guide athletes in their training as an easy-to-apply monitoring procedure during a standardized warm-up. A regular assessment including individual data history and statistical references for identification of response is recommended. Further data are necessary to confirm the results in a larger and more homogeneous population.

Individualizing the Throwing Progression Following Injury in Baseball Pitchers: the Past, Present, and Future

PURPOSE OF REVIEW

A critical component of any rehabilitation program following injury is a graduated exposure of pathologic or vulnerable tissue to sport-specific stressors. A foundational aspect in the return to sport process following an injury in baseball athletes is the development of an interval throwing program. A shift has occurred in recent years from generic programs to individualized progressions. The current review explores the evolution of interval throwing program construction and discusses the possibilities of the future with advancements in technology and understanding.

RECENT FINDINGS

Early interval throwing programs relied primarily on pre-determined throwing distance and volume to estimate total training load while following a fixed throwing schedule. Currently, clinicians have begun to utilize available technology in attempts to determine training prescription and obtain more accurate estimates of stresses placed upon the body. Thus, interval throwing programs have become more individualized and flexible to account for each athlete's individual differences and biological response to training. Future development may be able to predict specific internal response to stressors and proactively adjust training load to maximize positive adaptations while minimizing any maladaptive events. As with all concepts and principles within the realm of athlete rehabilitation, clinicians must continue to adapt how they conceptualize and develop individualized interval throwing programs for the overhead throwing athlete. We will continue to see a shift away from a responsive approach to a proactive one, where clinicians can utilize modern technologies to precisely prescribe a throwing dosage based upon expected tissue response within the athlete.

Acute Neuromuscular and Hormonal Responses to Power, Strength, and Hypertrophic Protocols and Training Background

This study investigated how two slightly different athlete groups would differ in acute neuromuscular and endocrine responses to specific resistance exercise loadings and recovery compared to untrained participants. Power athletes (PA, n = 8), strength athletes (SA, n = 8) and non-athletes (NA, n = 7) performed power (PL, 7 × 6 × 50% of 1RM), maximal strength (MSL, 7 × 3 × 3RM), and hypertrophic (HL, 5 × 10 × 10RM) loadings in Smith-machine back-squat. Neuromuscular performance, serum testosterone, growth hormone, and cortisol concentrations, and blood lactate (BL) were measured before (Pre), at Mid and after (Post) loading, and after recovery for 24 and 48 h. All loadings led to acute decreases in neuromuscular performance and elevations in hormone concentrations and BL. During PL, a significant group × time interactions occurred in maximal isometric force [F_{(4, 40)} = 4.189, p = 0.006, ηp2 = 0.295] indicating a greater decrease in PA compared to SA from Pre to Mid (p < 0.05), and in countermovement jump height [F_{(4, 40)} = 2.895, p = 0.034, ηp2 = 0.224] indicating a greater decrease in NA compared to SA from Pre to Mid (p < 0.05). During HL, growth hormone was higher in Mid and Post in SA compared to NA (p < 0.05). No significant interactions were found during recovery. The differences during PL and HL suggest that the training background may enhance acute responses during the present loadings, whereas it seemed to have a limited effect on the recovery.

The Current State of Subjective Training Load Monitoring: Follow-Up and Future Directions

This article addresses several key issues that have been raised related to subjective training load (TL) monitoring. These key issues include how TL is calculated if subjective TL can be used to model sports performance and where subjective TL monitoring fits into an overall decision-making framework for practitioners. Regarding how TL is calculated, there is conjecture over the most appropriate (1) acute and chronic period lengths, (2) smoothing methods for TL data and (3) change in TL measures (e.g., training stress balance (TSB), differential load, acute-to-chronic workload ratio). Variable selection procedures with measures of model-fit, like the Akaike Information Criterion, are suggested as a potential answer to these calculation issues with examples provided using datasets from two different groups of elite athletes prior to and during competition at the 2016 Olympic Games. Regarding using subjective TL to model sports performance, further examples using linear mixed models and the previously mentioned datasets are provided to illustrate possible practical interpretations of model results for coaches (e.g., ensuring TSB increases during a taper for improved performance). An overall decision-making framework for determining training interventions is also provided with context given to where subjective TL measures may fit within this framework and the determination if subjective measures are needed with TL monitoring for different sporting situations. Lastly, relevant practical recommendations (e.g., using validated scales and training coaches and athletes in their use) are provided to ensure subjective TL monitoring is used as effectively as possible along with recommendations for future research.

Submaximal Fitness Tests in Team Sports: A Theoretical Framework for Evaluating Physiological State

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.

Quantifying Fatigue in the Rugby Codes: The Interplay Between Collision Characteristics and Neuromuscular Performance, Biochemical Measures, and Self-Reported Assessments of Fatigue

Locomotor and collision actions that rugby players complete during match-play often lead to substantial fatigue, and in turn, delays in recovery. The methods used to quantify post-match fatigue and recovery can be categorised as subjective and objective, with match-related collision characteristics thought to have a primary role in modulating these recovery measures. The aim of this review was to (1) evaluate how post-match recovery has been quantified in the rugby football codes (i.e., rugby league, rugby union, and rugby sevens), (2) to explore the time-course of commonly used measures of fatigue post-match, and (3) to investigate the relationships between game-related collisions and fatigue metrics. The available evidence suggests that upper-, and lower-body neuromuscular performance are negatively affected, and biomarkers of muscular damage and inflammation increase in the hours and days following match-play, with the largest differences being at 12–36 h post-match. The magnitude of such responses varies within and between neuromuscular performance (Δ ≤ 36%, n = 13 studies) and tissue biomarker (Δ ≤ 585%, n = 18 studies) measures, but nevertheless appears strongly related to collision frequency and intensity. Likewise, the increase in perceived soreness in the hours and days post-match strongly correlate to collision characteristics across the rugby football codes. Within these findings, there are specific differences in positional groups and recovery trajectories between the codes which relate to athlete characteristics, and/or locomotor and collision characteristics. Finally, based on these findings, we offer a conceptual model of fatigue which details the multidimensional latent structure of the load to fatigue relationship contextualised to rugby. Research to date has been limited to univariate associations to explore relationships between collision characteristics and recovery, and multivariate methods are necessary and recommended to account for the latent structures of match-play external load and post-match fatigue constructs. Practitioners should be aware of the typical time windows of fatigue recovery and utilise both subjective and objective metrics to holistically quantify post-match recovery in rugby.