International Survey of training load monitoring practices in competitive swimming: How, what and why not?

Author(s):  
Lorna Barry ◽  
Mark Lyons ◽  
Karen McCreesh ◽  
Cormac Powell ◽  
Tom Comyns
Sports ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 109
Author(s):  
Tom Douchet ◽  
Allex Humbertclaude ◽  
Carole Cometti ◽  
Christos Paizis ◽  
Nicolas Babault

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s−2 (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s−2 (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.


2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Junqiang Qiu ◽  
Mingxing Li ◽  
Longyan Yi ◽  
Zhaoran Hou ◽  
Fan Yang ◽  
...  

Objective Training monitoring has become an integral component of total athlete training. Systematically monitoring the physiological and biochemical variables related to performance helps coaches and athletes to measure the effectiveness of their training programs and decide how to revise or update those programs, especially in swimming training. The key purpose of this study is to evaluate the physical function characteristics during preparation season and stress response during competition training sessions in 2017, and provides the helpful data for scientific training for the implementation of the preparation process. Methods During the preparation period, the National Swimming Team athletes were planed to screen and test the physical function characteristics. There are 39 male athletes and 37 female athletes to participate in the study. Body composition was assessed with dual energy X-ray (DXA). Anthropometric characteristics were assessed using Anthroscan 3D VITUS body scanner, and pulmonary function test using CHEST portable lung function meter(HI-101). During the competition period, the training load monitoring targets were 2 elite players who participated in XVII World Aquatics Championship in Budapest-2017 and the National Games 2017. The monitoring methods mainly included: blood tests (including Hb, CK, BU, testosterone, cortisol and ferritin etc.) were used to monitor the athlete's fitness functional status, and the Z-score method was used to express the index changes of two athletes; blood lactate was used to monitor the training load of athletes, and urine indexes were used to monitor body fluid balance and fatigue. Results 1. During the preparation period, the weight of male athletes is 78.4±8.2kg, the percentage of body fat is 15.9±2.8%, the weight of female athletes is 64.8±6.6kg, and the percentage of body fat is 24.2±3.5%. The vital capacity(VC) was 6.65±0.87 L for males and 4.86±0.69 L for females, the value of forced vital capacity(FVC) was 4.29±1.33 L for males and 3.43±0.96 L for females, and the mean value of ventilation per minute was 148.1±23.12 L for males and 110.4 ± 19.67 L for females. 2. During the competition preparation period, Z score was used to express the blood indicators of two athletes, before the XVII World Aquatics Championship in Budapest-2017, the Z score of Hb, T, T/C ratio and ferritin were (-0.5, 0, -0.4, 1.1) and (-0.8, -0.1, -1.0, 0), respectively. Before the competition of the National Games, the Z scores were (1.0, 0.3, 0.7, 0.6) and (1.4, 1.0, 0.1, -0.6) respectively. 3. Training load monitoring was carried out using the blood lactate control test, as the training load increased, the athletes' performance improved and the lactate level increased slightly. 4. The urine indicator test is used to observe the athlete's dehydration and recovery. On the second morning after the intensive training day, both athletes were negative for urine protein and with normal urine specific gravity. Conclusions 1. The screen and tests about the physical function characteristics of swimming athletes during preparation period is useful to develop a personalized training plan; 2. Z-score is easy and feasible for the elite swimmers to monitoring physical fitness capabilities, and higher Z-score is related with better athletic performance; 3. Blood lactate control test can be used for the training intensity monitoring of swimmers, athletes show higher levels of lactic acid metabolism and higher athletic performance before the competition.


2018 ◽  
Vol 13 (7) ◽  
pp. 947-952 ◽  
Author(s):  
Luka Svilar ◽  
Julen Castellano ◽  
Igor Jukic ◽  
David Casamichana

Purpose: To study the structure of interrelationships among external-training-load measures and how these vary among different positions in elite basketball. Methods: Eight external variables of jumping (JUMP), acceleration (ACC), deceleration (DEC), and change of direction (COD) and 2 internal-load variables (rating of perceived exertion [RPE] and session RPE) were collected from 13 professional players with 300 session records. Three playing positions were considered: guards (n = 4), forwards (n = 4), and centers (n = 5). High and total external variables (hJUMP and tJUMP, hACC and tACC, hDEC and tDEC, and hCOD and tCOD) were used for the principal-component analysis. Extraction criteria were set at an eigenvalue of greater than 1. Varimax rotation mode was used to extract multiple principal components. Results: The analysis showed that all positions had 2 or 3 principal components (explaining almost all of the variance), but the configuration of each factor was different: tACC, tDEC, tCOD, and hJUMP for centers; hACC, tACC, tCOD, and hJUMP for guards; and tACC, hDEC, tDEC, hCOD, and tCOD for forwards are specifically demanded in training sessions, and therefore these variables must be prioritized in load monitoring. Furthermore, for all playing positions, RPE and session RPE have high correlation with the total amount of ACC, DEC, and COD. This would suggest that although players perform the same training tasks, the demands of each position can vary. Conclusion: A particular combination of external-load measures is required to describe the training load of each playing position, especially to better understand internal responses among players.


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Jacob R. Gdovin ◽  
Riley Galloway ◽  
Lorenzo S. Tomasiello ◽  
Michael Seabolt ◽  
Robert Booker

Author(s):  
Joana F. Reis ◽  
Catarina N. Matias ◽  
Francesco Campa ◽  
José P. Morgado ◽  
Paulo Franco ◽  
...  

Background and aim: Monitoring bioelectric phase angle (PhA) provides important information on the health and the condition of the athlete. Together with the vector length, PhA constitutes the bioimpedance vector analysis (BIVA) patterns, and their joint interpretation exceeds the limits of the evaluation of the PhA alone. The present investigation aimed to monitor changes in the BIVA patterns during a training macrocycle in swimmers, trying to ascertain if these parameters are sensitive to training load changes across a 13-week training period. Methods: Twelve national and international level swimmers (four females; eight males; 20.9 ± 1.9 years; with a competitive swimming background of 11.3 ± 1.8 years; undertaking 16–20 h of pool training and 4–5 h of dry-land training per week and 822.0 ± 59.0 International Swimming Federation (FINA) points) were evaluated for resistance (R) and reactance (Xc) using a single frequency phase sensitive bioimpedance device at the beginning of the macrocycle (M1), just before the beginning of the taper period (M2), and just before the main competition of the macrocycle (M3). At the three-time assessment points, swimmers also performed a 50 m all-out first stroke sprint with track start (T50 m) while time was recorded. Results: The results of the Hotelling T2 test showed a significant vector displacement due to simultaneous R and Xc changes (p < 0.001), where shifting from top to bottom along the major axis of the R-Xc graph from M1 to M2 was observed. From M2 to M3, a vector displacement up and left along the minor axis of the tolerance ellipses resulted in an increase in PhA (p < 0.01). The results suggest a gain in fluid with a decrease in cellular density from M1 to M2 due to decrements in R and Xc. Nevertheless, the reduced training load characterizing taper seemed to allow for an increase in PhA and, most importantly, an increase of Xc, thus demonstrating improved cellular health and physical condition, which was concomitant with a significant increase in the T50 m performance (p < 0.01). Conclusions: PhA, obtained by bioelectrical R and Xc, can be useful in monitoring the condition of swimmers preparing for competition. Monitoring BIVA patterns allows for an ecological approach to the swimmers’ health and condition assessment without resorting to equations to predict the related body composition variables.


2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Joseph O. C. Coyne ◽  
G. Gregory Haff ◽  
Aaron J. Coutts ◽  
Robert U. Newton ◽  
Sophia Nimphius

2008 ◽  
Vol 13 (S1) ◽  
pp. 406-411 ◽  
Author(s):  
Mario Berges ◽  
Ethan Goldman ◽  
H. Scott Matthews ◽  
Lucio Soibelman

2017 ◽  
Vol 12 (s2) ◽  
pp. S2-42-S2-49 ◽  
Author(s):  
Andrew Murray

While historically adolescents were removed from their parents to prepare to become warriors, this process repeats itself in modern times but with the outcome being athletic performance. This review considers the process of developing athletes and managing load against the backdrop of differing approaches of conserving and maximizing the talent available. It acknowledges the typical training “dose” that adolescent athletes receive across a number of sports and the typical “response” when it is excessive or not managed appropriately. It also examines the best approaches to quantifying load and injury risk, acknowledging the relative strengths and weaknesses of subjective and objective approaches. Making evidence-based decisions is emphasized, while the appropriate monitoring techniques are determined by both the sporting context and individual situation. Ultimately a systematic approach to training-load monitoring is recommended for adolescent athletes to both maximize their athletic development and allow an opportunity for learning, reflection, and enhancement of performance knowledge of coaches and practitioners.


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