Exercise Training for Performance and Health

Foster, Carl; Porcari, John P.; Koning, Jos J. de; Bannwarth, E.; Casolino, Erika; Condello, Giancarlo; Gamalback, K; Gibson, Mark; Lueck, Justine; Rodríguez-Marroyo, José A.; Walraven, Lee

doi:10.5960/dzsm.2011.066

Cited by 9 publications

(10 citation statements)

References 15 publications

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“…32 Because of its simplicity, sRPE (which was anticipated by Gastin contemporaneously with first publication of sRPE 31 and used to plan and periodize the training of Australian Football players) has become widely used. [33][34][35][36][37] Because of the simplicity of sRPE, it has been possible to use it to analyze the data derived to examine the relationship between training load and performance 5 and to demonstrate that derived variables such as monotony and strain contribute to maladaptive responses to training. 38 There has been interest for many years in whether responses during submaximal exercise could serve as surrogate markers of how Figure 4 -Schematic of running speed versus heart rate (HR) and blood lactate.…”

Section: The Presentmentioning

confidence: 99%

“…In particular, the integration of elements already considered as part of the internal training load into single constructs seem likely to be of importance. For example, we know that the total training load, [4][5][6]53 the training intensity distribution pattern 23,24,37 and the day-to-day variation in training load (eg, monotony) 37,57,58 are independently related to performance. Is there a method of integrating these factors into a single variable that is capable of predicting the response (both good and bad) to training?…”

Section: The Presentmentioning

confidence: 99%

“…This story provides the historical grounding for the quest to understand the training response, most uniquely characterized by the concept of progression of the training load, and to the idea that training loads can be quantitatively expressed 1 and related to performance outcomes. [2][3][4][5][6] Although it is not known if Milo had a coach, most top athletes throughout history have had one, someone with more knowledge and experience, and the objectivity to evaluate their training and performance. The concept of training monitoring, regardless of historical time frame is in essence about the coach-athlete interface.…”

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Monitoring Training Loads: The Past, the Present, and the Future

Foster

Rodríguez-Marroyo

Koning³

2017

International Journal of Sports Physiology and Performance

197

152

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Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO 2 , and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved. Watching athletes perform well, set personal records or win competitions, are great pleasures for sports scientists. To think that the information that you have collected on the athlete, or synthesized from the literature, has helped the athlete achieve optimal performance is "as good as it gets" for support staff. Conversely, watching a poor performance inspires analysis of what went wrong, with preparation, tactics, or execution of the competitive plan. This provides the basis for the questions that drive sport-science research. Because so much of the preparation of athletes is related to the structure and details of the training program, there is a natural emphasis on how training influences performance. This interest goes into history, to Milo of Crotona, the Italian farm boy who lifted a growing bullock daily until he became the strongest man in the world and legend of the ancient Olympics. This story provides the historical grounding for the quest to understand the training response, most uniquely characterized by the concept of progression of the training load, and to...

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Section: The Presentmentioning

confidence: 99%

Section: The Presentmentioning

confidence: 99%

mentioning

confidence: 99%

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Monitoring Training Loads: The Past, the Present, and the Future

Foster

Rodríguez-Marroyo

Koning³

2017

International Journal of Sports Physiology and Performance

197

152

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“…First, training makes you better, and within limits, more training creates a larger effect. However, there clearly is a saturation curve to the training load versus improvement relationship (11)(12)(13). Just as there is evidence of highly individual responses to training from the Heritage Family Study (14) and elsewhere (15,16), there likely is an upper limit to the training load versus improvement relationship, which is likely highly individually specific.…”

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confidence: 99%

Polarized Training Is Optimal for Endurance Athletes: Response to Burnley, Bearden, and Jones

Foster

Casado

Esteve-Lanao³

et al. 2022

Medicine &Amp; Science in Sports &Amp; Exercise

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“…10 Although producing different absolute values for the computed training load (sRPE × duration), the between scale behavior of different versions of the RPE scales have been shown to be well-correlated markers of relative intensity, hence the internal training load. 11,12 The RPE represents the overall sense of exertion either at a certain moment 2,13 during sustained exercise, [14][15][16] or after an entire training session. 3,7,8 During incremental exercise, RPE typically increases in proportion to the relative muscular power output.…”

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confidence: 99%

Evidence That Rating of Perceived Exertion Growth During Fatiguing Tasks is Scalar and Independent of Exercise Mode

Meyer¹,

Bruenig²,

Cortis³

et al. 2022

International Journal of Sports Physiology and Performance

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Introduction: The relationship between the percentage of a fatiguing ambulatory task completed and rating of perceived exertion (RPE) appears to be linear and scalar, with a relatively narrow “window.” Recent evidence has suggested that a similar relationship may exist for muscularly demanding tasks. Methods: To determine whether muscularly demanding tasks fit within this “ambulatory window,” we tested resistance-trained athletes performing bench press and leg press with different loadings predicted to allow 5, 10, 20, and 30 repetitions and measured RPE (category ratio scale) at the end of the concentric action for each repetition. Results: There was a regular, and strongly linear, pattern of growth of RPE for both bench press (r = .89) and leg press (r = .90) during the tasks that allowed 5.2 (1.2), 11.6 (1.9), 22.7 (2.0), and 30.8 (3.2) repetitions for bench press and 5.5 (1.5), 11.4 (1.6), 20.2 (3.0), and 32.4 (4.2) repetitions for leg press, respectively. Conclusions: The path of the RPE growth versus percentage task fit within the window evident for ambulatory tasks. The results suggest that the RPE versus percentage task completed relationship is scalar, relatively linear, and apparently independent of exercise mode.

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Exercise Training for Performance and Health

Cited by 9 publications

References 15 publications

Monitoring Training Loads: The Past, the Present, and the Future

Monitoring Training Loads: The Past, the Present, and the Future

Polarized Training Is Optimal for Endurance Athletes: Response to Burnley, Bearden, and Jones

Evidence That Rating of Perceived Exertion Growth During Fatiguing Tasks is Scalar and Independent of Exercise Mode

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