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22 December, 2020

Apps to assess and monitor athletic performance

Team sports performance

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The routine monitoring of training loads and athletes’ fitness is an essential process to ensure an optimal performance progression. Scientific evidence shows us different valid methods for this purpose. For instance, professional teams have access to accelerometers, such as WIMU, to measure the external training load, encoders to measure strength and contact platforms or electric photocells to measure jumping or sprint capacity. However, these tools are technically complex or expensive, making its use difficult for most teams.

Nowadays, the mobile phone has become almost an extension of our body. Almost everybody has a smartphone which functions as a phone, but it also includes a camera, pedometer, GPS and many more features. In the last few years, a series of mobile applications have also been developed, which could facilitate the day to day of the coaching staff.

 Internal Load and Heart Rate Variability

There are many methods to assess the external load an athlete is being subject to, which usually consider both intensity (for example, speed) and the duration of the session. However, it is important to also know the physiological response (internal load) before such loads. In this sense, apart from the perceived effort or other variables such as heart rate, one of the most popular internal load markers in recent years is the heart rate variability (HRV). The HRV is based on the study of the variability in the interval between heartbeats. Summarizing in a simple way, high variability is associated with increased parasympathetic activation (i.e., a state of rest), while low variability is associated with greater sympathetic activation, and therefore, greater stress.

The HRV is usually used to see how athletes respond to training loads. Besides, it has been observed that managing training loads based on the athlete’s daily HRV (for example, prescribing higher loads when there is high HRV and reducing loads when the HRV is low) can be beneficial for performance compared to traditional programmed loads.1,2 There are different apps such as EliteHRV, that allow to connect a pulse oximeter to the athletes’ smartphone so they can track their HRV on a daily basis, being able to also track other subjective internal load variables, such as the quality of sleep or the level of perceived fatigue. It is important to mention that, in the case of EliteHRV, HRV values provided have shown to be highly correlated with those of other systems broadly used in scientific literature, which suggests that this is a valid device to monitor tendencies in HRV within training.3

Jumping Capacity

Jumping capacity has emerged as one of the simplest, yet most reliable markers to assess physical performance, particularly muscle power. Various researchers led by Dr. Gonzalez-Badillo have shown that the loss of height of a jump could be used as a fatigue indicator during training, as this variable is highly related to the loss of speed during strength series4 and with the loss of speed during repeated sprint sessions,5 which also shows the metabolic stress produced.

Therefore, these results show the great applicability of the jumping capacity measurement to assess muscle power or to determine the moment in which an exercise should be finished. Different apps such as MyJump, created by Dr. Balsalobre, facilitate the assessment of jump height (and other related variables, such as the strength-speed profile or the contact time in a Drop Jump) using only a cell phone camera. This application has been validated by comparing it to other more complex and expensive tools such as strength platforms, and the results share similar values with small differences of only ~1 cm  .6 Jean-Benoît Morin, one of the researchers who proposed the strength-speed profile estimation of the jump height has created an open access Excel sheet, to help determine this profile by introducing simple variables such as the jump height and weight.

Speed of Execution and Strength

Another variable that has become popular during the last few years for performance monitoring is the speed of execution in strength exercises. Several studies have shown that, to obtain greater benefits at a neuromuscular level, performing the repetitions as fast as possible is recommended, as moving the same load (whether low or high), at greater speed will mean exerting greater strength. These studies have also shown that if speed loss is avoided during strength series, more benefits might be obtained than with greater speed losses (which means to get close to muscle failure), as well as also avoiding adaptations such as muscle hypertrophy, which could be harmful in some sports, such as those involving jumps or sprints.7,8

Furthermore, by assessing the speed of execution with sub-maximum loads, we can also estimate the maximum load with which the athlete can perform a single repetition (known as 1RM), one of the most popular indicators of muscle strength. This is because the relative load and speed follow an essentially linear relationship, as the load increases approaching our 1RM the speed of execution will be lower. Therefore, as the speed associated with 1RM is relatively constant for the same exercise in different people, and knowing the speed at which we move different loads, we can estimate the load that would correspond to our 1RM through linear regression.9

Monitoring the speed of execution during strength exercises is recommended both to optimise training and to assess the improvements in muscle strength. For that, there are many methods available, with linear encoders or 3D capture systems being validated at a scientific level. There are apps such as MyLift, which facilitate determining the speed of execution and estimating de 1RM when recording the movement with the cell phone camera. Two studies assessing seven different devices to measure the speed of execution and the 1RM in strength exercises have shown that the app MyLift was valid compared to other devices used in the scientific field, such as linear encoders.10,11 However, a recent study concluded that its validity was considerably lower than that of other devices (with a variation coefficient of around 6% and a maximum mistake in the 1RM estimation of 19-25%).12 Therefore, there are mobile applications to estimate the speed of execution and the 1RM, although the suitability for use may depend partly on the level of accuracy expected and the experience in its management.

Hamstrings Strength

As we have mentioned in previous articles, hamstring injuries are one of the most frequent injuries in sports that include great accelerations of the lower limb, such as sprints or striking a football. Assessing the strength of this muscle group will be especially important to avoid potential injuries. For instance, a study published in the prestigious American Journal of Sports Medicine analysed the hamstrings eccentric strength for 178 Rugby Union players, and then tracked the prevalence of injuries during a season. The researchers observed that a greater imbalance (>15-20%) between legs was associated with a 2-3 times greater risk of suffering hamstring injury, especially if the athlete had previously suffered that same injury.13

The technology used for hamstring strength measurement in scientific studies is expensive, that’s why mobile apps such as “Nordics” have been developed, which allow us to assess the eccentric hamstrings strength through the recording of the Nordics hamstring exercise. For this assessment, we have to record with the smartphone camera the execution of the Nordics hamstring exercise and determine the angle in which the athlete cannot hold his own weight (break point angle). This measurement has been correlated to other technologies such as strength measurement with dynamometres,14,15 and therefore, it can be a practical alternative to assess athletes. This technology has allowed FC Barcelona to assess the progression of the hamstrings strength in some of its players during the confinement caused by the pandemic,16 which shows the practicality of this strategy.

Sprints

Speed is another basic component in any sport, and because of that, sprint measurement is one of the pillars in the assessments of most athletes. Although the ability to sprint has been traditionally assessed with tools as basic as a chronometer, currently, some of the most used methods for its scientific validity are the electric photocells (devices that automatically detect when the athlete cuts the light beam when running) or radar guns. Similarly, to what we have mentioned, there are mobile apps which can facilitate sprint measurement with no need of expensive equipment. The MySprint app allows to record a sprint with the phone camera (as long as the camera sampling frequency is high enough, >240 fps) and determine the speed reached at different points during the sprint. This application has been validated comparing it to the values provided by electric photocells (average difference of 0,002 seconds) 17. As it also allows to assess the speed at different points during a sprint, MySprint estimates the strength, speed and maximum power values achieved during the exercise, as well as the decrease in the strength application as the distance covered increases, providing values similar to those obtained with a radar gun.17

Change of Direction

The change of direction is an essential component in many sports, including both team sports (for example, football, rugby, hockey) and individual ones (for example, tennis). Its assessment is as important as the sprint capacity assessment. In the scientific field, contact platform equipment or electric photocells have been used to assess the performance in the change of direction, but we also have more practical and affordable methods available. For instance, the CODTimer app allows assessing the change of direction in one of the most popular tests, the 5+5. This test consists of covering 5 metres, performing a change of direction of 180° as fast as possible, and covering the 5 metres back again. By recording the test with this application (with a camera with at least 240 fps) we can determine manually when the athlete starts and finishes the test (when he crosses the line that indicates the beginning and the end). A study in which FC Barcelona’s physical trainer Marc Madruga-Parera participated, the times obtained with this application were correlated and very similar to those obtained by electric photocells.18 The app also showed to be equally valid to assess the asymmetries between legs (determined as the difference in time when performing the change of direction with one or the other leg).

Conclusions

As we can see, we have many validated tools available which could ease the assessment of the training load and physical performance of athletes even when the budget is tight and no other equipment such as linear encoders, strength platforms or photoelectric cells are available. However, it is important to highlight that the accuracy of these mobile apps may depend partly on how we handle them, so it is especially important to be careful and become familiar with their use.

 

Pedro Valenzuela

 

References

  1. Vesterinen V, Nummela A, Heikura I, et al. Individual Endurance Training Prescription with Heart Rate Variability. Vol 48.; 2016. doi:10.1249/MSS.0000000000000910
  2. Javaloyes A, Sarabia JM, Lamberts RP, Moya-Ramon M. Training prescription guided by heart-rate variability in cycling. Int J Sports Physiol Perform. 2019;14(1):23-32. doi:10.1123/ijspp.2018-0122
  3. Perrotta AS, Jeklin AT, Hives BA, Meanwell LE, Warburton DER. Validity of the Elite HRV Smartphone Application for Examining Heart Rate Variability in a Field-Based Setting. J strength Cond Res. 2017;31(8):2296-2302. doi:10.1519/JSC.0000000000001841
  4. Sánchez-Medina L, González-Badillo JJ. Velocity loss as an indicator of neuromuscular fatigue during resistance training. Med Sci Sport Exerc. 2011;43(9):1725-1734. doi:10.1249/MSS.0b013e318213f880
  5. Jiménez-Reyes P, Pareja-Blanco F, Cuadrado-Peñafiel V, Morcillo JA, Párraga JA, González-Badillo JJ. Mechanical, Metabolic and Perceptual Response during Sprint Training. Int J Sports Med. 2016;37(10):807-812.
  6. Balsalobre-Fernández C, Glaister M, Lockey RA. The validity and reliability of an iPhone app for measuring vertical jump performance. J Sports Sci. 2015;33(15):1574-1579. doi:10.1080/02640414.2014.996184
  7. Pareja-Blanco F, Rodríguez-Rosell D, Sánchez-Medina L, et al. Effects of velocity loss during resistance training on athletic performance, strength gains and muscle adaptations. Scand J Med Sci Sport. 2016;(1998):1-12. doi:10.1111/sms.12678
  8. Galiano C, Pareja-Blanco F, Hidalgo de Mora J, Sáez de Villarreal E. Low-Velocity Loss Induces Similar Strength Gains to Moderate-Velocity Loss During Resistance Training. J Strength Cond Res. 2020;(12):1. doi:10.1519/jsc.0000000000003487
  9. González-Badillo J, Sánchez-Medina L. Movement velocity as a measure of loading intensity in resistance training. Int J Sports Med. 2010;31:347-352.
  10. Pérez-Castilla A, Piepoli A, Delgado-García G, Garrido-Blanca G, García-Ramos A. Reliability and concurrent validity of seven commercially available devices for the assessment of movement velocity at different intensities during the bench press. J Strength Cond Res. 2019;33(5):1258-1265. doi:10.1519/jsc.0000000000003118
  11. Pérez-Castilla A, Piepoli A, Garrido-Blanca G, Delgado-García G, Balsalobre-Fernández C, García-Ramos A. Precision of 7 commercially available devices for predicting bench-press 1-repetition maximum from the individual load–velocity relationship. Int J Sports Physiol Perform. 2019;14(10):1442-1446. doi:10.1123/ijspp.2018-0801
  12. Martínez-Cava A, Hernandez-Belmonte A, Couriel-Ibáñez J, Morán-Navarro R, Gonzalez-Badillo JJ, Pallarés JG. Reliability of technologies to measure the barbell velocity : Implications for monitoring resistance training. PLoS One. 2020;In press:1-17. doi:10.1371/journal.pone.0232465
  13. Bourne MN, Opar DA, Williams MD, Shield AJ. Eccentric knee flexor strength and risk of hamstring injuries in rugby union. Am J Sports Med. 2015;43(11):2663-2670. doi:10.1177/0363546515599633
  14. Lee JWY, Li C, Yung PSH, Chan KM. The reliability and validity of a video-based method for assessing hamstring strength in football players. J Exerc Sci Fit. 2017;15(1):18-21. doi:10.1016/j.jesf.2017.04.001
  15. Sconce E, Jones P, Turner E, Comfort P, Graham-Smith P. The Validity of the Nordic Hamstring Lower for a Field-Based Assessment of Eccentric Hamstring Strength. J Sport Rehabil. 2015;24(1):13-20. doi:10.1123/jsr.2013-0097
  16. Moreno-Pérez V, Del Coso J, Romero-Rodríguez D, Marcé-Hernández L, Peñaranda M, Madruga-Parera M. Effects of home confinement due to COVID-19 pandemic on eccentric hamstring muscle strength in football players. Scand J Med Sci Sport. 2020;30(10):2010-2012. doi:10.1111/sms.13768
  17. Romero-Franco N, Jiménez-Reyes P, Castaño-Zambudio A, et al. Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods. Eur J Sport Sci. 2017;17(4):386-392. doi:10.1080/17461391.2016.1249031
  18. Balsalobre-fernández C, Bishop C, Beltrán-garrido JV, Cecilia-gallego P, Cuenca-amigó A, Romero-rodríguez D. The validity and reliability of a novel app for the measurement of change of direction performance. J Sports Sci. 2019;00(00):1-5. doi:10.1080/02640414.2019.1640029

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