Quantification method influences training load change in high school cross-country runners across a competitive season

Author(s):  
Micah C. Garcia ◽  
Brett S. Pexa ◽  
Kevin R. Ford ◽  
Mitchell J. Rauh ◽  
David M. Bazett-Jones

Abstract Context: Running programs traditionally monitor external loads (e.g., time, distance). There has been a recent movement to encompass a more comprehensive approach to also monitor training loads that account for internal loads (e.g., intensity, measured as session rating of perceived exertion [sRPE]). The combination of an external and internal load accounts for the potential interaction between these loads. While differences in weekly change in training loads have been reported between external loads and the combination of an external and internal load during 2- and 4-week training cycles, there are no reports whether these differences are apparent during an entire cross-country season in high school runners. Objective: To compare change in training loads, as measured by external loads and combinations of an external and internal load, in high school runners during an interscholastic cross-country season. Design: Case-series. Setting: Community-based with daily online surveys. Participants: Twenty-four high school cross-country runners (female=14, male=10, age=15.9±1.1 years, running experience=9.9±3.2 years). Main Outcome Measure(s): Week-to-week percent change in training load when measured by external loads (time, distance) and the combination of an external and internal load (timeRPE, distanceRPE). Results: Overall, the average weekly change was 7.1% greater for distanceRPE compared to distance (p=.04, d=0.18). When decreasing weekly running duration, the average weekly change was 5.2% greater for distanceRPE compared to timeRPE (p=.03, d=0.24). When maintaining or increasing weekly running duration, the average weekly change was 10–15% greater when an external load was combined with an internal load compared to external loads alone, but these differences were non- significant (p=.11–.22, d=0.19–0.34). Conclusions: Our results demonstrate that progression in training load may be underestimated when relying solely on external loads. The interaction between internal loads (sRPE) and external loads (distance or time) appears to provide a different measure of training stresses experienced by runners than external loads alone.

Author(s):  
Megan R Ryan ◽  
Christopher Napier ◽  
Daniel Greenwood ◽  
Max R Paquette

Training load is commonly used to monitor training stress and is the product of external and internal physiological loads experienced by an athlete. With emerging wearable technology, it is possible to evolve existing external load measurement from duration or distance to runner-specific biomechanical data, which when combined with existing measures of internal load such as session rating of perceived exertion (sRPE), may improve the quantification of training stress. This study compared week-to-week changes in training duration with different training loads obtained from common and more individualized measures of external load. The training of nine male high school cross-country runners from the same team undertaking the same training program was monitored for two consecutive weeks. This two-week cycle included a “coach-prescribed” low and high training load week. Training loads were calculated with sRPE and external load measures including: duration (minutes), Step Count, “Bone Stimulus” (IMeasureU), and cumulative vertical force. Weekly distances (in miles) were also measured. Between-week percent change (%Δ) was compared among training loads and minutes using paired t-tests and Cohen’s d effect size. Different %Δ were found between sRPExMinutes (%Δ=65 ± 25%; p = 0.002, d = 1.83), sRPExStep Count (%Δ=66 ± 31%; p = 0.006, d = 2.06), sRPExForce (%Δ=66 ± 29%; p = 0.002, d = 1.91), and miles (%Δ=28 ± 13%; p = 0.019, d = 0.71) compared to minutes (%Δ=20 ± 8%). These findings highlight that only using weekly volume can greatly misrepresent changes in training stress in runners. We therefore encourage coaches and practitioners to consider training monitoring approaches beyond just weekly distance or duration. Simple measures of training load that include duration and sRPE might be sufficient.


Author(s):  
Montgomery Bertschy ◽  
Jeffrey T Howard ◽  
Sakiko Oyama ◽  
Tianou Zhang ◽  
Kelly Cheever

This study aimed to examine the effectiveness of presession subjective wellness, measured by a mobile application, in predicting the rating of perceived exertion (RPE) and training load for collegiate female soccer players throughout all training sessions of a competitive season. Thirty-three training sessions over 10 weeks involving 23 subjects were analyzed. Before each training session, players self-reported wellness measurements (sleep quality, stress, mood, soreness, fatigue, and sleep duration) through a mobile application questionnaire. Training load (active time, distance, GPS session load, and sprint score) was measured by GPS. RPE was self-reported immediately after training sessions. Generalized estimating equations found that presession wellness scores had a significant effect on postsession RPE. A 1 point increase in the wellness score corresponded with a significant increase in RPE ([Formula: see text] = 0.4[Formula: see text], 95% CI (0.05–0.91), p = 0.029). Wellness component of mood had a significant effect on RPE as noted by a 1 SD increase that corresponded to an increase in RPE ([Formula: see text] = 0.[Formula: see text], 95% CI (0.07–0.30), p = 0.001). Psychosocial component of wellness (mood) played the most influential role in predicting RPE. The results suggest that monitoring student-athlete wellness may be helpful in regulating player internal load, and increasing player mood may also lower internal load.


Author(s):  
Bernardo Ide ◽  
Amanda Silvatti ◽  
Craig Staunton ◽  
Moacir Marocolo ◽  
Dustin Oranchuk ◽  
...  

The International System of Units (SI) was adopted in 1960 as a universal measuring system to be used for all areas of science. Sports Science papers have shown lots of inaccurate and inappropriate terms for quantification of athletes’ performance and the psychobiological responses to exercise (e.g., internal load). In biomechanics, external and internal loads are forces acting externally and internally, inducing stress and strain in the biological tissues. Therefore, the current review present simple proposals to correct the inappropriate terms: 1) do not use the term external load when referring to the assessment of exercise time, distance, displacement, speed, velocity, acceleration, torque, work, power, impulse, etc.; 2) do not use the term internal load when referring to the assessment of psychobiological stress markers (i.e., session rating of perceived exertion, heart rate, blood lactate, oxygen consumption, etc.); 3) do not use the term impulse when expressing other calculus than integrating force with respect to time, and neither strain, when expressing other phenomena than the body deformation. Instead, the term exercise intensity is universal and can be used to describe all forms of exercise. Finally, duration should precisely be described according to physical quantities (e.g., time, distance, displacement, speed, velocity, acceleration, force, torque, work, power, impulse, etc.) and the units accomplish by use of the SI. These simple quantifications can be performed for the exercises, sessions, microcycles, mesocycles and macrocycles of the athletes. Such standardization will provide a consistent and clear communication among sports scientists and all areas of science.


2020 ◽  
Vol 55 (12) ◽  
pp. 1285-1291 ◽  
Author(s):  
Christopher Napier ◽  
Megan Ryan BSc ◽  
Carlo Menon ◽  
Max R. Paquette

Context Historically, methods of monitoring training loads in runners have used simple and convenient metrics, including the duration or distance run. Changes in these values are assessed on a week-to-week basis to induce training adaptations and manage injury risk. To date, whether different measures of external loads, including biomechanical measures, provide better information regarding week-to-week changes in external loads experienced by a runner is unclear. In addition, the importance of combining internal-load measures, such as session rating of perceived exertion (sRPE), with different external-load measures to monitor week-to-week changes in training load in runners is unknown. Objective To compare week-to-week changes in the training loads of recreational runners using different quantification methods. Design Case series. Setting Community based. Patients or Other Participants Recreational runners in Vancouver, British Columbia. Main Outcome Measure(s) Week-to-week changes in running time, steps, and cumulative shock, in addition to the product of each of these variables and the corresponding sRPE scores for each run. Results Sixty-eight participants were included in the final analysis. Differences were present in week-to-week changes for running time compared with timeRPE (d = 0.24), stepsRPE (d = 0.24), and shockRPE (d = 0.31). The differences between week-to-week changes in running time and cumulative shock were also significant at the overall group level (d = 0.10). Conclusions We found that the use of an internal training-load measure (sRPE) in combination with external load (training duration) provided a more individualized estimate of week-to-week changes in overall training stress. A better estimation of training stress has significant implications for monitoring training adaptations, resulting performance, and possibly injury risk reduction. We therefore recommend the regular use of sRPE and training duration to monitor training load in runners. The use of cumulative shock as a measure of external load in some runners may also be more valid than duration alone.


Author(s):  
Erik P. Andersson ◽  
Irina Hämberg ◽  
Paulo Cesar Do Nascimento Salvador ◽  
Kerry McGawley

Abstract Purpose This study aimed to compare physiological factors and cycle characteristics during cross-country (XC) roller-skiing at matched inclines and speeds using the double-poling (DP) and diagonal-stride (DS) sub-techniques in junior female and male XC skiers. Methods Twenty-three well-trained junior XC skiers (11 women, 12 men; age 18.2 ± 1.2 yr.) completed two treadmill roller-skiing tests in a randomized order using either DP or DS. The exercise protocols were identical and included a 5 min warm-up, 4 × 5 min submaximal stages, and an incremental test to exhaustion, all performed at a 5° incline. Results No significant three-way interactions were observed between sex, submaximal exercise intensity, and sub-technique. For the pooled sample, higher values were observed for DP versus DS during submaximal exercise for the mean oxygen uptake kinetics response time (33%), energy cost (18%), heart rate (HR) (9%), blood lactate concentration (5.1 versus 2.1 mmol·L−1), rating of perceived exertion (12%), and cycle rate (25%), while cycle length was lower (19%) (all P < 0.001). During the time-to-exhaustion (TTE) test, peak oxygen uptake ($$\dot{V}$$ V ˙ O2peak), peak HR, and peak oxygen pulse were 8%, 2%, and 6% lower, respectively, for DP than DS, with a 29% shorter TTE during DP (pooled data, all P < 0.001). Conclusion In well-trained junior XC skiers, DP was found to exert a greater physiological load than DS during uphill XC roller-skiing at submaximal intensities. During the TTE test, both female and male athletes were able to ski for longer and reached markedly higher $$\dot{V}$$ V ˙ O2peak values when using DS compared to DP.


Author(s):  
Alice Iannaccone ◽  
Daniele Conte ◽  
Cristina Cortis ◽  
Andrea Fusco

Internal load can be objectively measured by heart rate-based models, such as Edwards’ summated heart rate zones, or subjectively by session rating of perceived exertion. The relationship between internal loads assessed via heart rate-based models and session rating of perceived exertion is usually studied through simple correlations, although the Linear Mixed Model could represent a more appropriate statistical procedure to deal with intrasubject variability. This study aimed to compare conventional correlations and the Linear Mixed Model to assess the relationships between objective and subjective measures of internal load in team sports. Thirteen male youth beach handball players (15.9 ± 0.3 years) were monitored (14 training sessions; 7 official matches). Correlation coefficients were used to correlate the objective and subjective internal load. The Linear Mixed Model was used to model the relationship between objective and subjective measures of internal load data by considering each player individual response as random effect. Random intercepts were used and then random slopes were added. The likelihood-ratio test was used to compare statistical models. The correlation coefficient for the overall relationship between the objective and subjective internal data was very large (r = 0.74; ρ = 0.78). The Linear Mixed Model using both random slopes and random intercepts better explained (p < 0.001) the relationship between internal load measures. Researchers are encouraged to apply the Linear Mixed Models rather than correlation to analyze internal load relationships in team sports since it allows for the consideration of the individuality of players.


Author(s):  
Sullivan Coppalle ◽  
Guillaume Ravé ◽  
Jason Moran ◽  
Iyed Salhi ◽  
Abderraouf Ben Abderrahman ◽  
...  

This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p =0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p =0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.


2011 ◽  
Vol 43 (Suppl 1) ◽  
pp. 664
Author(s):  
Matthew M. Sundby ◽  
Allie L. Jentz ◽  
Jenna M. Hersant ◽  
Danielle M. Beilke ◽  
Jeff Sauter ◽  
...  

Author(s):  
Alexandru Nicolae Ungureanu ◽  
Corrado Lupo ◽  
Gennaro Boccia ◽  
Paolo Riccardo Brustio

Purpose: The primary aim of this study was to evaluate whether the internal (session rating of perceived exertion [sRPE] and Edwards heart-rate-based method) and external training load (jumps) affect the presession well-being perception on the day after (ie, +22 h), according to age and tactical position, in elite (ie, Serie A2) female volleyball training. Methods: Ten female elite volleyball players (age = 23 [4] y, height = 1.82 [0.04] m, body mass = 73.2 [4.9] kg) had their heart rate monitored during 13 team (115 individual) training sessions (duration: 101 [8] min). Mixed-effect models were applied to evaluate whether sRPE, Edwards method, and jumps were correlated (P ≤ .05) to Hooper index factors (ie, perceived sleep quality/disorders, stress level, fatigue, and delayed-onset muscle soreness) in relation to age and tactical position (ie, hitters, central blockers, opposites, and setters). Results: The results showed a direct relationship between sRPE (P < .001) and presession well-being perception 22 hours apart, whereas the relationship was the inverse for Edwards method internal training load. Age, as well as the performed jumps, did not affect the well-being perception of the day after. Finally, central blockers experienced a higher delayed-onset muscle soreness than hitters (P = .003). Conclusions: Findings indicated that female volleyball players’ internal training load influences the pretraining well-being status on the day after (+ 22 h). Therefore, coaches can benefit from this information to accurately implement periodization in a short-term perspective and to properly adopt recovery strategies in relation to the players’ well-being status.


2019 ◽  
Vol 14 (6) ◽  
pp. 847-849 ◽  
Author(s):  
Pedro Figueiredo ◽  
George P. Nassis ◽  
João Brito

Purpose: To quantify the association between salivary secretory immunoglobulin A (sIgA) and training load in elite football players. Methods: Data were obtained on 4 consecutive days during the preparation camp for the Rio 2016 Olympic Games. Saliva samples of 18 elite male football players were collected prior to breakfast. The session rating of perceived exertion (s-RPE) and external training-load metrics from global positioning systems (GPS) were recorded. Within-subject correlation coefficients between training load and sIgA concentration, and magnitude of relationships, were calculated. Results: sIgA presented moderate to large negative correlations with s-RPE (r = −.39), total distance covered (r = −.55), accelerations (r = −.52), and decelerations (r = −.48). Trivial to small associations were detected between sIgA and distance covered per minute (r = .01), high-speed distance (r = −.23), and number of sprints (r = −.18). sIgA displayed a likely moderate decrease from day 1 to day 2 (d = −0.7) but increased on day 3 (d = 0.6). The training-load variables had moderate to very large rises from day 1 to day 2 (d = 0.7 to 3.2) but lowered from day 2 to day 3 (d = −5.0 to −0.4), except for distance per minute (d = 0.8) and sprints (unclear). On day 3, all training-load variables had small to large increments compared with day 1 (d = 0.4 to 1.5), except for accelerations (d = −0.8) and decelerations (unclear). Conclusions: In elite football, sIgA might be more responsive to training volume than to intensity. External load such as GPS-derived variables presented stronger association with sIgA than with s-RPE. sIgA can be used as an additional objective tool in monitoring football players.


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