Training Impulse Research Articles

Correlation between training load variables and sports performance in elite athletes during a CrossTraining competition

Controlling training loads is important to obtain results and avoid overtraining in athletes. In CrossTraining, subjective perception of effort (PSE) has been cited as an important parameter for load control, however, little is known about the contribution of physiological parameters. The objective of this study was to investigate the correlations between training control variables and performance in elite athletes during a CrossTraining competition. Ten athletes (26.4 ± 4.5 years, 84.32 ± 6.75 kg, height 1.74 ± 0.21 m) participated in the study. The RPE values ​​were recorded at the end of each test, and the athletes were monitored in real time using a HR monitoring system (Firstbeat SPORT, Jyvaskyla, Finland). The training control variables collected were: Total training volume (VTT), PSE, training load (PSE X time), mean and maximum HR, average and training impulse (TRIMP). Pearson's correlation coefficient demonstrated the following associations with competitive performance (VTT, r=0.87; RPE, r=0.28; training load, r=0.60; HRmáx, r=0.73; HRmean, r=0.76 and TRIMP, r=0.87). In conclusion, physiological parameters showed significant correlations compared to RPE, being more suitable for monitoring CrossTraining athletes.

Physical demands and psychophysiological stress in young athletes team sports

Training monitoring is important in the development process of the athlete. The objective of the study was to characterize the psychophysiological response and physical demands of soccer, basketball, handball, and volleyball with young athletes. The sample consisted of 61 young athletes of both genders and members of team sports, 10 training sessions for each modality were monitored. The psychophysiological responses were monitored by the session rating perception of exertion (Session RPE) and training impulse (TRIMP). The physical demands were, distance covered (DC), DC by speed zone (DC_Z1, DC_Z2, DC_Z3, DC_Z4, DC_Z5), number of sprints, and duration of the session. In addition, the recovery status (TQR) was also collected. Differences were noted between duration (p<0.001), DC_Z1 (p<0.017), DC_Z2 (p<0.05), DC_Z3 (p<0.05), DC_Z4 (p<0.003), DC_Z5 (p < 0.05), sprints (p < 0.001), TRIMP (p<0.02), Session RPE (p<0.05) and TQR (p<0.007). In psychophysiological responses, handball showed more time in zones 4 and 5 than other modalities. According to physical demands, basketball, and handball had a higher number of sprints and also higher values in DP_Z5. Therefore, the simultaneous monitoring of physical demands and psychophysiological responses provides supplementary information in monitoring young athletes.

Semiautomatic Training Load Determination in Endurance Athletes

Background: Despite endurance athletes recording their training data electronically, researchers in sports cardiology rely on questionnaires to quantify training load. This is due to the complexity of quantifying large numbers of training files. We aimed to develop a semiautomatic postprocessing tool to quantify training load in clinical studies. Methods: Training data were collected from two prospective athlete’s heart studies (Master Athlete’s Heart study and Prospective Athlete Heart study). Using in-house developed software, maximal heart rate (MaxHR) and training load were calculated from heart rate monitored during cumulative training sessions. The MaxHR in the lab was compared with the MaxHR in the field. Lucia training impulse score, based on individually based exercise intensity zones, and Edwards training impulse, based on MaxHR in the field, were compared. A questionnaire was used to determine the number of training sessions and training hours per week. Results: Forty-three athletes recorded their training sessions using a chest-worn heart rate monitor and were selected for this analysis. MaxHR in the lab was significantly lower compared with MaxHR in the field (183 ± 12 bpm vs. 188 ± 13 bpm, p < .01), but correlated strongly (r = .81, p < .01) with acceptable limits of agreement (±15.4 bpm). An excellent correlation was found between Lucia training impulse score and Edwards training impulse (r = .92, p < .0001). The quantified number of training sessions and training hours did not correlate with the number of training sessions (r = .20) and training hours (r = −.12) reported by questionnaires. Conclusion: Semiautomatic measurement of training load is feasible in a wide age group. Standard exercise questionnaires are insufficiently accurate in comparison to objective training load quantification.

Impact of Fruit and Vegetable Enzyme Supplementation on Aerobic Performance and Lactate Response in Older Adults Following High-Intensity Interval Exercise Through Exergaming: Randomized Experimental Matched-Pair Study.

Exercise offers substantial health benefits but can induce oxidative stress and inflammation, especially in high-intensity formats such as high-intensity interval exercise (HIIE). Exergaming has become an effective, enjoyable fitness tool for all ages, particularly older adults. Enzyme supplements may enhance exercise performance by improving lactate metabolism and reducing oxidative stress. This study investigates the efficacy of fruit and vegetable enzyme supplementation in modulating fatigue and enhancing aerobic capacity in older adults following HIIE through exergaming. The study recruited 16 older adult female participants and allocated them into 2 distinct groups (enzyme and placebo) based on their pretest lactate levels. This division used pairwise grouping to guarantee comparability between the groups, ensuring the integrity of the results. They engaged in HIIE using Nintendo Switch Ring Fit Adventure, performing 8 sets of 20 seconds of maximum effort exercise interspersed with 30 seconds of rest, totaling 370 seconds of exercise. Key metrics assessed included blood lactate levels, heart rate, rating of perceived exertion, and training impulse. Participants in the enzyme group were administered a fruit and vegetable enzyme supplement at a dosage of 30 mL twice daily over a period of 14 days. The enzyme group showed significantly lower blood lactate levels compared to the placebo group, notably after the fourth (mean 4.29, SD 0.67 vs mean 6.34, SD 1.17 mmol/L; P=.001) and eighth (mean 5.84, SD 0.63 vs mean 8.20, SD 1.15 mmol/L; P<.001) exercise sessions. This trend continued at 5 minutes (mean 6.85, SD 0.82 vs mean 8.60, SD 1.13 mmol/L; P=.003) and 10 minutes (mean 5.91, SD 1.16 vs mean 8.21, SD 1.27 mmol/L; P=.002) after exercise. Although both groups exceeded 85% of their estimated maximum heart rate during the exercise, enzyme supplementation did not markedly affect the perceived intensity or effort. The study indicates that fruit and vegetable enzyme supplementation can significantly reduce blood lactate levels in older adults following HIIE through exergaming. This suggests a potential role for these enzymes in modulating lactate production or clearance during and after high-intensity exercise. These findings have implications for developing targeted interventions to enhance exercise tolerance and recovery in older adults.

Comparison between acute effects of β-alanine supplementation on psychophysiological scales, blood lactate, training impulse and heart rate variability during high-intensity functional training

Comparison between acute effects of β-alanine supplementation on psychophysiological scales, blood lactate, training impulse and heart rate variability during high-intensity functional training

Training Impulse and Its Impact on Load Management in Collegiate and Professional Soccer Players

Methods: Training impulse (TRIMP) is obtained through wearable technology and plays a direct role on the load management of soccer players. It is important to understand TRIMP to best prepare athletes for competition. A systematic search for articles was conducted using Google Scholar, with papers screened and extracted by five reviewers. The inclusion criteria were: the study was focused on collegiate or professional soccer, the use of training impulse (TRIMP), and the use of wearable technology to measure TRIMP. Of 10,100 papers, 10,090 articles were excluded through the systematic review process. Ten papers were selected for final review and grouped based on (1) training vs. match (N = 8/10), (2) preseason vs. in-season (N = 3/10), and (3) positional comparison (N = 3/10). Wearable technologies mainly track physical metrics (N = 10/10). Higher TRIMP data were noted in starters than reserves throughout the season in matches and slightly lower TRIMP for starters vs. reserves during training. TRIMP data change throughout the season, being higher in preseason phases compared to early-season, mid-season, and late-season phases. These findings help highlight the benefits of TRIMP in managing internal player load in soccer. Future research should focus on utilizing wearable-derived TRIMP and the impact on player performance metrics, and how TRIMP data vary across different positions in soccer.

Validity of Weekly and Monthly Perceived Exertion in Runners.

The development of the rating of perceived exertion (RPE) enables the easy assessment of runners' training strain as well as training load (TL). However, the long-term and retrospective validity of TL assessment using RPE scales still needs further investigation. Therefore, this study examined the validity of weekly and monthly ratings of perceived exertion (W-RPE, M-RPE) in assessing TL in runners. Healthy adult runners (n=53) rated perceived exertion using the modified category-ratio 10 (CR-10) scale for each week of a four-week period, as well as for the month, considering the four-week period. CR-10 for the week and the month were multiplied by the total training time of the week and month, respectively, to assess the W-RPE and M-RPE. Training impulse (TRIMP) was used as the criterion measure. The results indicated that the W-RPE and M-RPE may be used for monitoring TL during prolonged periods, presenting a very large correlations with the criterion measure.

Capturing the Complex Relationship Between Internal and External Training Load: A Data-Driven Approach.

Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable tool to capture and visualize this coupling. Using training load data in speed skating, we evaluated how well bivariate KDE plots describe the coupling of internal and external load and differentiate between specific training sessions, compared to training impulse scores or intensity distribution into training zones. On-ice training sessions of 18 young (sub)elite speed skaters were monitored for velocity and heart rate during 2 consecutive seasons. Training session types were obtained from the coach's training scheme, including endurance, interval, tempo, and sprint sessions. Differences in training load between session types were assessed using Kruskal-Wallis or Kolmogorov-Smirnov tests for training impulse and KDE scores, respectively. Training impulse scores were not different between training session types, except for extensive endurance sessions. However, all training session types differed when comparing KDEs for heart rate and velocity (both P < .001). In addition, 2D KDE plots of heart rate and velocity provide detailed insights into the (subtle differences in) coupling of internal and external training load that could not be obtained by 2D plots using training zones. 2D KDE plots provide a valuable tool to visualize and inform coaches on the (subtle differences in) coupling of internal and external training load for training sessions. This will help coaches design better training schemes aiming at desired training adaptations.

A semi-automatic tool to quantify training load in endurance athletes

Abstract Funding Acknowledgements Type of funding sources: None. Background Despite the widespread use of wearables in endurance sports allowing the measurements needed for quantification of the training load (TL), studies in sports cardiology consistently use less reliable questionnaires to assess TL.[1] This scant use of activity trackers to determine TL can be explained by the large workload for data analysis. Purpose We aimed to develop a semi-automated post-processing tool that allows quantifying TL, based on heart rate (HR) monitoring by commercial wearables, for future use in clinical and epidemiological studies. We compared the calculated maximal HR automatically derived from HR monitoring during endurance training with the maximal HR obtained during incremental exercise testing in the lab. We describe TL calculated by our tool in young and older endurances athletes and compare it with the TL obtained via questionnaires. Methods Training data was collected in two multicenter studies. Master@Heart is a cohort study of endurance trained middle-aged men between 45 and 70 years.[2] Pro@Heart is a prospective study in young endurance athletes between 16 and 23 years.[3] For the purpose of this substudy, 44 athletes (38 ± 17 years) that had recorded all their training sessions using a chest-worn HR monitor for one year were included. Using an in-house developed pipeline in R (R core Team, Vienna, Austria), maximal HR and TL were calculated from training data. The maximal HR measured in the field (Tangent MaxHR) was then compared with the lab-measured maximal HR (Lab MaxHR). Both Lucia training impulse (LuTRIMP) and Edwards TRIMP (eTRIMP) were compared as measures of TL based on HR-based intensity zones. LuTRIMP, based on individually based exercise intensity zones, and eTRIMP based on the Tangent MaxHR. Participants filled in a standard exercise questionnaire to determine the amount of training sessions and training hours per week. Results Lab MaxHR was lower than Tangent MaxHR (183 ± 12.2bpm vs. 188.3 ± 13.0bpm; Figure 1 A), but correlated strongly (r=0.81, P&amp;lt;0.01; Figure 1 B) with low mean bias (-5.3bpm, LOA±15.4; Figure 1 C). LuTRIMP and eTRIMP correlated very strong (r=0.93, P&amp;lt;0.01). Pro@Heart athletes performed a higher TL (1730 ± 644 vs. 1190 ± 314 AU/week, P&amp;lt;0.01; Figure 2 A), duration (12.2 ± 4.6 hours per week vs. 7.9 ± 2.4, P&amp;lt;0.01; Figure 2 B) and trained more frequent (5.9 ± 1.7 vs. 4.0 ± 1.0 sessions per week, P&amp;lt;0.01; Figure 2 C) than Master@Heart athletes. Neither the reported training sessions nor the training hours in the questionnaires correlated with the measured training sessions (r=0.20) and training hours respectively (r=0.12). Conclusion Our tool allows to semi-automatically quantify different TL parameters in endurance athletes from a wide age range. The use of questionnaires to determine TL is inaccurate. TL calculated using eTRIMP is comparable to TL calculated using LuTRIMP. Since eTRIMP does not require an exercise test, it is more easily implementable in large studies.

Assessment of stress response and its interrelationship with external load in female soccer players.

The study aimed to evaluate the physiological stress response, i.e. internal load to intermittent and continuous exercise performed during the treadmill running in professional female soccer players, and additionally to determine the most appropriate method for assessing load in the athletes. Six professional female athletes (age 25.3±1.8 years, height 168.4±2.7 cm, weight 64.8±5.8 kg, maximal oxygen consumption (V˙ O2max) 64±4.1 ml۰kg-1۰min-1, and heart rate (HRmax) 195±1.8 b.p.m.) performed a series of preseason treadmill tests. HR and V˙ O2max were measured in the athletes during intermittent load (increase and decrease of running time and treadmill speed) and an incremental load (gradual increases running time, treadmill speed and a treadmill incline angle). Banister's, Edwards', Stagno's and Lucia's training impulse (TRIMP) quantification methods were used to assess internal load. The relationships between V˙ O2max and above-mentioned TRIMPs load indicators were calculated using Pearson's correlation coefficient. Large, very large and near perfect correlations between TRIMP and V˙ O2max were observed during intermittent and incremental load (range r = 0.712 - 0.852 and r =563 - 930; p < 0.05, respectively). Correlations between other TRIMPs and V˙ O2max demonstrated moderate, small and negative small relationships. Changes in HR and oxygen consumption registered during intermittent or gradually increasing load conditions could be evaluated using the TRIMP method for both types of activities, and this method could potentially be useful for the testing of high-intensity intermittent physical fitness of players before the soccer season.

Internal and External Loads of Young Elite Soccer Players during Defensive Small-Sided Games.

The aim of this study was to evaluate the effects of different time periods on the internal and external loads of soccer players during small-sided games (SSGs). Seventeen young soccer players performed a SSG of 5 vs. 5 + 5 with 2 floaters, where two teams had possession of the ball, and one had to recover it. With established periods of 30 s (SSG30), 1 min (SSG1) or 2 min (SSG2), teams participated in a defensive role for these periods of time. Total distance covered, moderate speed running distance, high speed running distance, sprint running distance, accelerations, decelerations and Player Load were monitored using global positioning systems devices. The maximal heart rate and modified training impulse were monitored using heart rate monitors. The rating of perceived exertion (RPE) was also measured. Data showed a small increase between SSG30 and SSG1 in Player Load (ES = -0.35; p < 0.01), and a small increase in high speed running (ES = -0.41; p < 0.05) and sprinting (ES = -0.47; p < 0.01) between SSG30 and SSG2. Also, SSG1 showed a small increase in sprinting (ES = -0.57; p < 0.01) and accelerations (ES = -0.37; p < 0.05) with respect to SSG2. In addition, SSG2 showed a small increase in the RPE with respect to SSG30 (ES = 0.46; p < 0.05). The results indicate that shorter defensive periods in SSGs increased high speed running, while longer defensive periods promoted greater perceived exertion. Manipulation of the duration of defensive periods in SSGs is a variable that should be considered in soccer training.

Validity and Reliability of Facial Rating of Perceived Exertion Scales for Training Load Monitoring.

van der Zwaard, S, Hooft Graafland, F, van Middelkoop, C, and Lintmeijer, LL. Validity and reliability of facial rating of perceived exertion scales for training load monitoring. J Strength Cond Res 37(5): e317-e324, 2023-Rating of perceived exertion (RPE) is often used by coaches and athletes to indicate exercise intensity, which facilitates training load monitoring and prescription. Although RPE is typically measured using the Borg's category-ratio 10-point scale (CR10), digital sports platforms have recently started to incorporate facial RPE scales, which potentially have a better user experience. The aim of this study was to evaluate the validity and reliability of a 5-point facial RPE scale (FCR5) and a 10-point facial RPE scale (FCR10), using the CR10 as a golden standard and to assess their use for training load monitoring. Forty-nine subjects were grouped into 17 untrained (UT), 19 recreationally trained (RT), and 13 trained (T) individuals Subjects completed 9 randomly ordered home-based workout sessions (3 intensities × 3 RPE scales) on the Fitchannel.com platform. Heart rate was monitored throughout the workouts. Subjects performed 3 additional workouts to assess reliability. Validity and reliability of both facial RPE scales were low in UT subjects (intraclass correlation [ICC] ≤ 0.44, p ≤ 0.06 and ICC ≤ 0.43, p ≥ 0.09). In RT and T subjects, validity was moderate for FCR5 (ICC ≥ 0.72, p < 0.001) and good for FCR10 (ICC ≥ 0.80, p < 0.001). Reliability for these groups was rather poor for FCR5 (ICC = 0.51, p = 0.006) and moderate for FCR10 (ICC = 0.74, p < 0.001), but it was excellent for CR10 (ICC = 0.92, p < 0.001). In RT and T subjects, session RPE scores were also strongly related to Edward's training impulse scores ( r ≥ 0.70, p < 0.001). User experience was best supported by the FCR10 scale. In conclusion, researchers, coaches, strength and conditioning professionals, and digital sports platforms are encouraged to incorporate the valid and reliable FCR10 and not FCR5 to assess perceived exertion and internal training load of recreationally trained and trained individuals.

Training Load and Acute Performance Decrements Following Different Training Sessions.

To examine the differences in training load (TL) metrics when quantifying training sessions differing in intensity and duration. The relationship between the TL metrics and the acute performance decrement measured immediately after the sessions was also assessed. Eleven male recreational cyclists performed 4 training sessions in a random order, immediately followed by a 3-km time trial(TT). Before this period, participants performed the time TT in order to obtain a baseline performance. The difference in the average power output for the TTs following the training sessions was then expressed relative to the best baseline performance. The training sessions were quantified using 7 different TL metrics, 4 using heart rate as input, 2 using power output, and 1 using the rating of perceived exertion. The load of the sessions was estimated differently depending on the TL metrics used. Also, within the metrics using the same input (heart rate and power), differences were found. TL using the rating of perceived exertion was the only metric showing a response that was consistent with the acute performance decrements found for the different training sessions. The Training Stress Score and the individualized training impulse demonstrated similar patterns but overexpressed the intensity of the training sessions. The total work done resulted in an overrepresentation of the duration of training. TL metrics provide dissimilar results as to which training sessions have higher loads. The load based on TL using the rating of perceived exertion was the only one in line with the acute performance decrements found in this study.

The contributing external load factors to internal load during small-sided games in professional rugby union players.

This study aimed to investigate which external load variables were associated with internal load during three small-sided games (SSG) in professional rugby union players. Forty professional rugby union players (22 forwards, 18 backs) competing in the English Gallagher Premiership were recruited. Three different SSGs were designed: one for backs, one for forwards, and one for both backs and forwards. General linear mixed-effects models were implemented with internal load as dependent variable quantified using Stagno's training impulse, and external load as independent variables quantified using total distance, high-speed (>61% top speed) running distance, average acceleration-deceleration, PlayerLoad™, PlayerLoad™ slow (<2 m·s-1), number of get-ups, number of first-man-to-ruck. Internal load was associated with different external load variables dependent on SSG design. When backs and forwards were included in the same SSG, internal load differed between positional groups (MLE = -121.94, SE = 29.03, t = -4.20). Based on the SSGs investigated, practitioners should manipulate different constraints to elicit a certain internal load in their players based on the specific SSG design. Furthermore, the potential effect of playing position on internal load should be taken into account in the process of SSG design when both backs and forwards are included.

Effects of a training intervention tailored to the menstrual cycle on endurance performance, recovery and well-being in female recreational runners – A randomized-controlled pilot study

Effects of a training intervention tailored to the menstrual cycle on endurance performance, recovery and well-being in female recreational runners – A randomized-controlled pilot study

Validity and reliability of the physiological and perceptual responses elicited during a novel treadmill-based Soccer Referee Simulation (SRS)

PurposeThis study explored the validity and reliability of the physiological and perceptual responses elicited during a novel treadmill-based Soccer Referee Simulation (SRS).MethodsFollowing the collection of baseline measures and habituation procedures, eight sub-elite soccer referees completed a single trial of the SRS whereby measures of heart rate (HR), oxygen uptake (V̇O2), blood lactate concentrations ([La−]b), and differential ratings of perceived exertion (RPE) were obtained. Referees’ HR responses were also monitored during a series of competitive matches (5 match observations per referee). For the reliability aspect of the investigation, eight well-trained males with soccer playing experience and a comparable physiological profile were initially habituated, and thereafter completed three separate trials of the SRS during which the reliability of the selected outcome variables were ascertained. Trials were separated by 3–7 days and performed under standardised conditions.ResultsNo differences were evidenced between the SRS and match play in relation to measures of mean HR (P = 0.444; ES = 0.29), peak HR (P = 0.074; ES = 0.74), or HR-based training impulse (P = 0.498; ES = 0.25). Additionally, no systematic differences were detected between reliability trials for any of the measured outcome variables (P ≥ 0.293), whilst good levels of reliability were observed for measures of mean HR (ICC = 0.94; CV = 3.1%), peak HR (ICC = 0.93; CV = 2.2%), HR-based training impulse (ICC = 0.95; CV = 10.0%), mean V̇O2 (ICC = 0.95; CV = 2.6%); [La−]b (ICC ≥ 0.89; CV ≤ 11.5%), and differential RPE (ICC ≥ 0.94; CV ≤ 15.1%).ConclusionThe SRS represents a valid and reliable protocol that closely replicates the physiological and decision-making demands of soccer refereeing.

Physiological Demands of a Self-Paced Firefighter Air-Management Course and Determination of Work Efficiency

To assess the physiological demands of an AMC and examine differences across BMI categories. A secondary aim was to develop an equation to assess work efficiency in firefighters. Fifty-seven firefighters (Women, n = 4; age: 37.2 ± 8.4 yr.; height: 182.0 ± 6.9 cm; body mass: 90.8 ± 13.1 kg; BMI: 27.8 ± 3.6 kg·m-2) completed an AMC per routine evaluation while wearing a department issued self-contained breathing apparatus and full protective gear. Course completion time, starting pounds per square inch (PSI) on the air cylinder, changes in PSI, and distance traveled were recorded. All firefighters were equipped with a wearable sensor integrated with a triaxial accelerometer and telemetry to assess movement kinematics, heart rate, energy expenditure, and training impulse. The AMC consisted of an initial section involving a hose line advance, rescue (body drag), stair climb, ladder raise, and forcible entry. This section was followed by a repeating loop, which consisted of a stair climb, search, hoist, and recovery walk. Firefighters repeated the course loop until the self-contained breathing apparatus air supply pressure reached 200 PSI, at which time they were instructed to lay down until the PSI reached zero. Average completion time was 22.8 ± 1.4 min, with a mean distance of 1.4 ± 0.3 km and an average velocity of 2.4 ± 1.2 m·s-1. Throughout the AMC, the mean heart rate was 158.7 ± 11.5 bpm equating to 86.8 ± 6.3% of the age-predicted max heart rate and a training impulse of 55 ± 3 AU. Mean energy expenditure was 464 ± 86 kcals and work efficiency was 49.8 ± 14.9 km·PSI-1·s. Regression analysis determined that fat-free mass index (R2 = 0.315; β = -5.069), body fat percentage (R2 = 0.139; β = -0.853), fat-free mass (R2 = 0.176; β = -0.744), weight (R2 = 0.329; β = -0.681), and age (R2 = 0.096; β = -0.571) were significant predictors of work efficiency. The AMC is a highly aerobic task with near-maximal heart rates reached throughout the course. Smaller and leaner individuals achieved a higher degree of work efficiency during the AMC.

Differences and variability of physical and technical characteristics among rugby union small-sided games performed within a preseason

This study aimed to investigate the differences in physical and technical characteristics among three specific rugby union small-sided games (SSG) and to examine the variability of these characteristics over three weeks within a preseason of a professional rugby union club. Eighteen backs and 22 forwards were recruited for the study. The three SSG designs were: backs only (SSG-B), forwards only (SSG-F) and both backs and forwards (SSG-BF). Physical characteristics were quantified using external (e.g., total distance covered [m·min−1]) and internal (i.e., Stagno's training impulse [AU·min−1]) load measures. Technical characteristics were quantified using the number of rucks, successful passes, unsuccessful passes, line breaks and tries per minute. The SSG-BF produced a greater high speed (&gt;61%) running distance covered in comparison with SSG-B (1.97 vs. 1.32 m·min−1) and SSG-F (1.26 vs. 0.94 m·min−1), and more successful passes (9.47 vs. 9.36 count·min−1) and line breaks (0.98 vs. 0.65 count·min−1) than SSG-F. Conversely, all the other physical and technical characteristics were higher in SSG-B and SSG-F. All the physical and technical characteristics, except high speed (&gt;61%) distance covered in forwards and unsuccessful passes and tries per minute, changed over days showing either a linear or quadratic pattern. Based on these findings, practitioners may implement position-specific SSG (i.e., SSG-B and SSG-F) to expose players to greater physical and technical characteristics. Furthermore, if SSGs were to be repeated across multiple days, practitioners should be aware of the possible variability in physical and technical characteristics due to potential adaptations to the constraints or the onset of fatigue.

The effect of pitch size manipulation during small sided-games performed by different age category football players: a pilot study

This research aimed to analyse the pitch size manipulation effect on internal and external load and to study the age effect on the studied variables in different small-sided games (SSGs) formats. Male U-12 (n = 8), U-15 (n = 8) youth football players, and U-23 (n = 8) professional cohorts participated in the study. Two SSGs formats were analyzed, goalkeeper (GK) + 4 vs. 4 + GK, 3 minutes play in 20 × 30 m and 24 × 36 m, with 3 minutes rest between bouts. The variance analysis Anova two-way was used to analyse two independent factors, pitch size, and age group. The playing area manipulation had an effect under the following variables: distance (p &lt; 0.001), speed 0–6 km/h (p &lt; 0.001), speed 12–18 km/h (p &lt; 0.001), speed 18–21 km/h (p &lt; 0.001), accelerations (Ac.) 1–2 m/s2(p &lt; 0.001), decelerations (Dc.) 2–3 m/s2 (p &lt; 0.001), metabolic power (Pmet) (p &lt; 0.001) and high metabolic load distance (HMLD) (p &lt; 0.001). The age group influenced the distance covered (p &lt; 0.001), speed 0–6 km/h (p &lt; 0.001), speed 6–12 km/h (p &lt; 0.001), speed 12–18 km/h (p &lt; 0.001), speed 21–24 km/h (p = 0.030), Ac. 1–2 m/s2 (p &lt; 0.001), Ac. 1–2 m/s2 (p &lt; 0.001Pmet (p &lt; 0.001), HMLD (p &lt; 0.001) and training impulse (TRIMP)(p &lt; 0.001). Playing area manipulation in football SSGs promotes an increase in external load intensity, namely, larger areas are suitable for larger effects at high speeds (&gt;21 km/h) and TRIMP. A careful and detailed evaluation of training tasks, considering the different age category football players, is important to optimize the planning in football, aiming at improving players’ condition and performance and avoiding health problems and injuries.

Physical, physiological demands and movement profiles of professional men’s field hockey games

The aim of this study was to investigate the physical demands, physiological demands, and movement profiles of different positions across four quarters in professional men’s field hockey games. Eighteen professional male field hockey players participated in the study, and data were collected in eleven official matches. Players wore global positioning system units and heart rate monitors to collect physical, physiological, and movement profile data. Defenders had significantly higher absolute total distance covered, player load, acceleration and deceleration count, and forward-backward initial movement analysis (IMA) count, but lower high speed running distance, compared with midfielders and forwards (p&amp;lt;.05). However, when using relative metrics (normalised by playing time), defenders had the lowest physical and physiological outputs, and forwards were the highest (p&amp;lt;.05). Total distance covered per minute, high-speed running distance per minute, player load per minute, acceleration and deceleration count per minute, and repeated high-intensity efforts per minute were all significantly higher in quarter 1 than in other three quarters (p&amp;lt;.05). The percentages of linear running and non-linear dynamic movement duration decreased quarter by quarter. Modified training impulse per minute reached its peak in quarter 2 (p&amp;lt;.05). It was concluded that defenders had the highest volume in terms of the game demands due to their high playing minutes; however, they had the lowest relative volume compared with other two positions. Forwards had the highest linear running intensity, while midfielders were required to perform more multi-directional, non-linear movements. Quarter 1 was the most active quarter and players became fatigued in quarter 2. IMA counts were not sensitive to fatigue compared to movement profile and modified training impulse variables.