PerPot: A metamodel for simulation of load performance interaction

Validity and Accuracy of Impulse-Response Models for Modeling and Predicting Training Effects on Performance of Swimmers

PURPOSE

The aim of this study was to compare the suitability of models for practical applications in training planning.

METHODS

We tested six impulse-response models, including Banister's model (Model Ba), a variable dose-response model (Model Bu), and indirect-response models differing in the way they account or not for the effect of previous training on the ability to respond effectively to a given session. Data from 11 swimmers were collected during 61 wk across two competitive seasons. Daily training load was calculated from the number of pool-kilometers and dry land workout equivalents, weighted according to intensity. Performance was determined from 50-m trials done during training sessions twice a week. Models were ranked on the base of Aikaike's information criterion along with measures of goodness of fit.

RESULTS

Models Ba and Bu gave the greatest Akaike weights, 0.339 ± 0.254 and 0.360 ± 0.296, respectively. Their estimates were used to determine the evolution of performance over time after a training session and the optimal characteristics of taper. The data of the first 20 wk were used to train these two models and predict performance for the after 8 wk (validation data set 1) and for the following season (validation data set 2). The mean absolute percentage error between real and predicted performance using Model Ba was 2.02% ± 0.65% and 2.69% ± 1.23% for validation data sets 1 and 2, respectively, and 2.17% ± 0.65% and 2.56% ± 0.79% with Model Bu.

CONCLUSIONS

The findings showed that although the two top-ranked models gave relevant approximations of the relationship between training and performance, their ability to predict future performance from past data was not satisfactory for individual training planning.

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

A conceptual framework has a central role in the scientific process. Its purpose is to synthesize evidence, assist in understanding phenomena, inform future research and act as a reference operational guide in practical settings. We propose an updated conceptual framework intended to facilitate the validation and interpretation of physical training measures. This revised conceptual framework was constructed through a process of qualitative analysis involving a synthesis of the literature, analysis and integration with existing frameworks (Banister and PerPot models). We identified, expanded, and integrated four constructs that are important in the conceptualization of the process and outcomes of physical training. These are: (1) formal introduction of a new measurable component 'training effects', a higher-order construct resulting from the combined effect of four possible responses (acute and chronic, positive and negative); (2) explanation, clarification and examples of training effect measures such as performance, physiological, subjective and other measures (cognitive, biomechanical, etc.); (3) integration of the sport performance outcome continuum (from performance improvements to overtraining); (4) extension and definition of the network of linkages (uni and bidirectional) between individual and contextual factors and other constructs. Additionally, we provided constitutive and operational definitions, and examples of theoretical and practical applications of the framework. These include validation and conceptualization of constructs (e.g., performance readiness), and understanding of higher-order constructs, such as training tolerance, when monitoring training to adapt it to individual responses and effects. This proposed conceptual framework provides an overarching model that may help understand and guide the development, validation, implementation and interpretation of measures used for athlete monitoring.

Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer

BACKGROUND

In professional senior soccer, training load monitoring is used to ensure an optimal workload to maximize physical fitness and prevent injury or illness. However, to date, different training load indicators are used without a clear link to training outcomes.

OBJECTIVE

The aim of this systematic review was to identify the state of knowledge with respect to the relationship between training load indicators and training outcomes in terms of physical fitness, injury, and illness.

METHODS

A systematic search was conducted in four electronic databases (CINAHL, PubMed, SPORTDiscus, and Web of Science). Training load was defined as the amount of stress over a minimum of two training sessions or matches, quantified in either external (e.g., duration, distance covered) or internal load (e.g., heart rate [HR]), to obtain a training outcome over time.

RESULTS

A total of 6492 records were retrieved, of which 3304 were duplicates. After screening the titles, abstracts and full texts, we identified 12 full-text articles that matched our inclusion criteria. One of these articles was identified through additional sources. All of these articles used correlations to examine the relationship between load indicators and training outcomes. For pre-season, training time spent at high intensity (i.e., >90 % of maximal HR) was linked to positive changes in aerobic fitness. Exposure time in terms of accumulated training, match or combined training, and match time showed both positive and negative relationships with changes in fitness over a season. Muscular perceived exertion may indicate negative changes in physical fitness. Additionally, it appeared that training at high intensity may involve a higher injury risk. Detailed external load indicators, using electronic performance and tracking systems, are relatively unexamined. In addition, most research focused on the relationship between training load indicators and changes in physical fitness, but less on injury and illness.

CONCLUSION

HR indicators showed relationships with positive changes in physical fitness during pre-season. In addition, exposure time appeared to be related to positive and negative changes in physical fitness. Despite the availability of more detailed training load indicators nowadays, the evidence about the usefulness in relation to training outcomes is rare. Future research should implement continuous monitoring of training load, combined with the individual characteristics, to further examine their relationship with physical fitness, injury, and illness.

Planning a sports training program using Adaptive Particle Swarm Optimization with emphasis on physiological constraints

Objective

An effective training plan is an important factor in sports training to enhance athletic performance. A poorly considered training plan may result in injury to the athlete, and overtraining. Good training plans normally require expert input, which may have a cost too great for many athletes, particularly amateur athletes. The objectives of this research were to create a practical cycling training plan that substantially improves athletic performance while satisfying essential physiological constraints. Adaptive Particle Swarm Optimization using ɛ-constraint methods were used to formulate such a plan and simulate the likely performance outcomes. The physiological constraints considered in this study were monotony, chronic training load ramp rate and daily training impulse.

Results

A comparison of results from our simulations against a training plan from British Cycling, which we used as our standard, showed that our training plan outperformed the benchmark in terms of both athletic performance and satisfying all physiological constraints.

Electronic supplementary material

The online version of this article (10.1186/s13104-017-3120-9) contains supplementary material, which is available to authorized users.

Cardiorespiratory Coordination in Repeated Maximal Exercise

Increases in cardiorespiratory coordination (CRC) after training with no differences in performance and physiological variables have recently been reported using a principal component analysis approach. However, no research has yet evaluated the short-term effects of exercise on CRC. The aim of this study was to delineate the behavior of CRC under different physiological initial conditions produced by repeated maximal exercises. Fifteen participants performed 2 consecutive graded and maximal cycling tests. Test 1 was performed without any previous exercise, and Test 2 6 min after Test 1. Both tests started at 0 W and the workload was increased by 25 W/min in males and 20 W/min in females, until they were not able to maintain the prescribed cycling frequency of 70 rpm for more than 5 consecutive seconds. A principal component (PC) analysis of selected cardiovascular and cardiorespiratory variables (expired fraction of O₂, expired fraction of CO₂, ventilation, systolic blood pressure, diastolic blood pressure, and heart rate) was performed to evaluate the CRC defined by the number of PCs in both tests. In order to quantify the degree of coordination, the information entropy was calculated and the eigenvalues of the first PC (PC1) were compared between tests. Although no significant differences were found between the tests with respect to the performed maximal workload (Wmax), maximal oxygen consumption (VO₂ max), or ventilatory threshold (VT), an increase in the number of PCs and/or a decrease of eigenvalues of PC₁ (t = 2.95; p = 0.01; d = 1.08) was found in Test 2 compared to Test 1. Moreover, entropy was significantly higher (Z = 2.33; p = 0.02; d = 1.43) in the last test. In conclusion, despite the fact that no significant differences were observed in the conventionally explored maximal performance and physiological variables (Wmax, VO₂ max, and VT) between tests, a reduction of CRC was observed in Test 2. These results emphasize the interest of CRC evaluation in the assessment and interpretation of cardiorespiratory exercise testing.

From an indirect response pharmacodynamic model towards a secondary signal model of dose-response relationship between exercise training and physical performance

The aim of this study was to test the suitability of using indirect responses for modeling the effects of physical training on performance. We formulated four different models assuming that increase in performance results of the transformation of a signal secondary to the primary stimulus which is the training dose. The models were designed to be used with experimental data with daily training amounts ascribed to input and performance measured at several dates ascribed to output. The models were tested using data obtained from six subjects who trained on a cycle ergometer over a 15-week period. The data fit for each subject was good for all of the models. Goodness-of-fit and consistency of parameter estimates favored the model that took into account the inhibition of production of training effect. This model produced an inverted-U shape graphic when plotting daily training dose against performance because of the effect of one training session on the cumulated effects of previous sessions. In conclusion, using secondary signal-dependent response provided a framework helpful for modeling training effect which could enhance the quantitative methods used to analyze how best to dose physical activity for athletic performance or healthy living.