The design and evaluation of an integrated training load and injury/illness surveillance system in competitive swimming

OBJECTIVE

To design and evaluate an integrated training load monitoring and injury/illness surveillance system in a competitive swimming environment.

DESIGN

Descriptive/mixed methods.

SETTING

Swim Ireland National Training Centres.

PARTICIPANTS

Fourteen competitive athletes and seven coaches/medical data collectors participated in the evaluation process.

OUTCOME MEASURES

System satisfaction, usefulness and burden were evaluated. Barriers to the implementation and effectiveness of the system were explored.

RESULTS

Most athletes were 'extremely' or 'very' satisfied with the overall data collection process and also found it to be 'extremely' or 'very' useful in the training centre environment. All practitioners were 'extremely satisfied with the system and found it to be either 'extremely' or 'very' useful in their role. Process constraints and data access and control were significant themes related to the athletes, while practitioners highlighted communication and cooperation amongst stakeholders, layering context to the data, maintaining data integrity and the coach's influence in the monitoring process as being important to the monitoring/surveillance process.

CONCLUSIONS

Training load monitoring and injury/illness surveillance are necessary to elevate the standard of prospective injury/illness prevention research. Integrated systems should be designed in line with key consensus statements, while also being implemented in a way that counteracts the challenges within the real-world training environment.

Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice

Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.

Is a Head-Worn Inertial Sensor a Valid Tool to Monitor Swimming?

PURPOSE

This study aimed to independently validate a wearable inertial sensor designed to monitor training and performance metrics in swimmers.

METHODS

A total of 4 male (21 [4] y, 1 national and 3 international) and 6 female (22 [3] y, 1 national and 5 international) swimmers completed 15 training sessions in an outdoor 50-m pool. Swimmers were fitted with a wearable device (TritonWear, 9-axis inertial measurement unit with triaxial accelerometer, gyroscope, and magnetometer), placed under the swim cap on top of the occipital protuberance. Video footage was captured for each session to establish criterion values. Absolute error, standardized effect, and Pearson correlation coefficient were used to determine the validity of the wearable device against video footage for total swim distance, total stroke count, mean stroke count, and mean velocity. A Fisher exact test was used to analyze the accuracy of stroke-type identification.

RESULTS

Total swim distance was underestimated by the device relative to video analysis. Absolute error was consistently higher for total and mean stroke count, and mean velocity, relative to video analysis. Across all sessions, the device incorrectly detected total time spent in backstroke, breaststroke, butterfly, and freestyle by 51% (15%). The device did not detect time spent in drill. Intraclass correlation coefficient results demonstrated excellent intrarater reliability between repeated measures across all swimming metrics.

CONCLUSIONS

The wearable device investigated in this study does not accurately measure distance, stroke count, and velocity swimming metrics or detect stroke type. Its use as a training monitoring tool in swimming is limited.

Predicting Lactate Threshold With Rate of Perceived Exertion in Young Competitive Male Swimmers

The purpose of this study was to verify the effectiveness of the rate of perceived exertion threshold (RPET) for predicting young competitive swimmers' lactate threshold (LT) during incremental testing. We enrolled 13 male athletes (M age = 16, SD = 0.6 years) in an incremental test protocol consisting of eight repetitions of a 100-meter crawl with 2-minute intervals between each repetition. We collected data for blood lactate concentration ([La]) and Borg scale rate of perceived exertion (RPE) at the end of each repetition. The results obtained were: M RPET = 4.98, SD = 1.12 arbitrary units (A.U.) and M lactate threshold = 4.24, SD = 1.12 mmol.L^-1, with [La] and RPE identified by the maximal deviation (Dmax) method without a significant difference (p > 0.05) and large correlations between DmaxLa and DmaxRPE at variables for time (r = 0.64), velocity (r = 0.67) and percentage of personal best time (PB) (r = 0.60). These results suggest that RPET is a good predictor of LT in young competitive swimmers.

Monitoring the swimmer's training load: A narrative review of monitoring strategies applied in research

The high incidence of injury during swim training and the increasing demands of the sports make monitoring of the swimmer's training load a key concept requiring further investigation. Research has previously introduced numerous methods for the purposes of monitoring the swimmer's training load, but a narrative review discussing the strengths and limitations of each method is lacking. Consequently, this narrative review aims to summarize the monitoring strategies that have been applied in research on competitive swimmers. This knowledge can assist professionals in the field in choosing which method is appropriate in their particular setting. The results from this study showed that external training load was predominantly obtained through real-life observation of the swimmers' training volume. However, research has investigated a number of internal load monitoring tools, including blood lactate, training heart rate, and perceived effort of training. To date, blood lactate markers are still considered most accurate and especially recommended at higher levels of competitive swimming or for those at greater risk of injury. Further, mood state profiling has been suggested as an early indicator of overtraining and may be applied at the lower competitive levels of swimming. Professionals in the field should consider the individual, the aim of the current training phase, and additional logistical issues when determining the appropriate monitoring strategy in their setting.

Modeling the Prediction of the Session Rating of Perceived Exertion in Soccer: Unraveling the Puzzle of Predictive Indicators

PURPOSE

To predict the session rating of perceived exertion (sRPE) in soccer and determine its main predictive indicators.

METHODS

A total of 70 external-load indicators (ELIs), internal-load indicators, individual characteristics, and supplementary variables were used to build a predictive model.

RESULTS

The analysis using gradient-boosting machines showed a mean absolute error of 0.67 (0.09) arbitrary units (AU) and a root-mean-square error of 0.93 (0.16) AU. ELIs were found to be the strongest predictors of the sRPE, accounting for 61.5% of the total normalized importance (NI), with total distance as the strongest predictor. The included internal-load indicators and individual characteristics accounted only for 1.0% and 4.5%, respectively, of the total NI. Predictive accuracy improved when including supplementary variables such as group-based sRPE predictions (10.5% of NI), individual deviation variables (5.8% of NI), and individual player markers (17.0% of NI).

CONCLUSIONS

The results showed that the sRPE can be predicted quite accurately using only a relatively limited number of training observations. ELIs are the strongest predictors of the sRPE. However, it is useful to include a broad range of variables other than ELIs, because the accumulated importance of these variables accounts for a reasonable component of the total NI. Applications resulting from predictive modeling of the sRPE can help coaching staff plan, monitor, and evaluate both the external and internal training load.

Relation Between Training Load and Recovery-Stress State in High-Performance Swimming

Background: The relation between training load, especially internal load, and the recovery-stress state is of central importance for avoiding negative adaptations in high-performance sports like swimming. The aim of this study was to analyze the individual time-delayed linear effect relationship between training load and recovery-stress state with single case time series methods and to monitor the acute recovery-stress state of high-performance swimmers in an economical and multidimensional manner over a macro cycle. The Acute Recovery and Stress Scale (ARSS) was used for daily monitoring of the recovery-stress state. The methods session-RPE (sRPE) and acute:chronic workload-ratio (ACWR) were used to compare different methods for quantifying the internal training load with regard to their interrelationship with the recovery-stress state. Methods: Internal load and recovery-stress state of five highly trained female swimmers [with a training frequency of 13.6 ± 0.8 sessions per week and specializing in sprint (50 and 100 m), middle-distance (200 and 400 m), or long distance (800 and 1,500 m) events] were daily documented over 17 weeks. Two different types of sRPE were applied: RPE^∗duration (sRPE^h) and RPE^∗volume (sRPE^km). Subsequently, we calculated the ratios ACWR^h and ACWR^km (sRPE last week: 4-week exponentially weighted moving average). The recovery-stress state was measured by using the ARSS, consisting of eight scales, four of which are related to recovery [Physical Performance Capability (PPC), Mental Performance Capability (MPC), Emotional Balance (EB), Overall Recovery (OR)], and four to stress [Muscular Stress (MS), Lack of Activation (LA), Negative Emotional State (NES), Overall Stress (OS)]. To examine the relation between training load and recovery-stress state a cross correlation (CCC) was conducted with sRPE^h, sRPE^km, ACWR^h, and ACWR^km as lead and the eight ARSS-scales as lag variables. Results: A large variation of training load can be observed in the individual week-to-week fluctuations whereby the single fluctuations can significantly differ from the overall mean of the group. The range also shows that the CCC individually reaches values above 0.3, especially with sRPE^km as lead variable. Overall, there is a large range with significant differences between the recovery and stress dimensions of the ARSS and between the training load methods, with sRPE^km having the largest span (Range = 1.16). High inter-individual differences between the athletes lie in strength and direction of the correlation | 0.66|≤ CCC ≥|-0.50|. The time delayed effects (lags 0-7) are highly individual, however, clear patterns can be observed. Conclusion: The ARSS, especially the physical and overall-related scales (PPC, OR, MS, OS), is a suitable tool for monitoring the acute recovery-stress state in swimmers. MPC, EB, LA, and NES are less affected by training induced changes. Comparably high CCC and Ranges result from the four internal load methods, whereby sRPE, especially sRPE^km, shows a stronger relation to recovery-stress state than ACWR. Based on these results and the individual differences in terms of time delay in training response, we recommend for swimming to use sRPE to monitor the internal training load and to use the ARSS, with a focus at the physical and overall-scales, to monitor the recovery-stress state.

Training load quantification in elite swimmers using a modified version of the training impulse method

Prior reports have described the limitations of quantifying internal training loads using hear rate (HR)-based objective methods such as the training impulse (TRIMP) method, especially when high-intensity interval exercises are performed. A weakness of the TRIMP method is that it does not discriminate between exercise and rest periods, expressing both states into a single mean intensity value that could lead to an underestimate of training loads. This study was designed to compare Banister's original TRIMP method (1991) and a modified calculation procedure (TRIMPc) based on the cumulative sum of partial TRIMP, and to determine how each model relates to the session rating of perceived exertion (s-RPE), a HR-independent training load indicator. Over four weeks, 17 elite swimmers completed 328 pool training sessions. Mean HR for the full duration of a session and partial values for each 50 m of swimming distance and rest period were recorded to calculate the classic TRIMP and the proposed variant (TRIMPc). The s-RPE questionnaire was self-administered 30 minutes after each training session. Both TRIMPc and TRIMP measures strongly correlated with s-RPE scores (r = 0.724 and 0.702, respectively; P < 0.001). However, TRIMPc was ∼ 9% higher on average than TRIMP (117 ± 53 vs. 107 ± 47; P < 0.001), with proportionally greater inter-method difference with increasing workload intensity. Therefore, TRIMPc appears to be a more accurate and appropriate procedure for quantifying training load, particularly when monitoring interval training sessions, since it allows weighting both exercise and recovery intervals separately for the corresponding HR-derived intensity.

A descriptive analysis of internal and external loads for elite-level tennis drills

PURPOSE

Planning tennis sessions accentuating physical development requires an understanding of training load (TL). The aims were to describe the external and internal TL of drills and analyze relationships between ratings of perceived exertion (RPE), TL, and other measures.

METHODS

Fourteen elite-level junior tennis athletes completed 259 individual drills. Six coaches helped devise classifications for all drills: recovery/defensive, open pattern, accuracy, 2-on-1 open, 2-on-1 net play, closed technical, point play, and match play. Notational analysis on stroke and error rates was performed postsession. Drill RPE and mental exertion were collected postdrill, while heart rate (HR) was recorded continuously.

RESULTS

Recovery/defensive, open pattern, and point play were significantly greater than closed technical drills (P < .05) for RPE and mental exertion, as were accuracy drills and match play (P < .05). Recovery/defensive, open-pattern, accuracy, and 2-on-1 open drills had higher stroke rates than match play (P < .05). Error rates of closed technical drills were significantly higher than for open pattern, 2-on-1 drills, point play, and match play (P < .05). No HR differences were observed (P > .05) between categories. Substantial correlations existed for drill RPE and TL with mental exertion (r > .62) for several categories. TL was substantially correlated with total strokes (r > .65), while HR and stroke and error rates were in slight to moderate agreement with RPE and TL (r < .51).

CONCLUSIONS

Recovery/defensive drills are highest in physiological stress, making them ideal for maximizing physicality. Recovery/defensive drills compromised training quality, eliciting high error rates. In contrast, 2-on-1 net-play drills provided the lowest error rates, potentially appropriate for error-amelioration practice. Open-pattern drills were characterized by significantly higher stroke rates, suggesting congruence with high-repetition practice. Finally, with strong relationships between physical and mental perception, mental exertion may complement currently used monitoring strategies (TL and RPE).