• Thomas Wheeler

Over monitoring and under-reaching

Monitoring athlete performance and wellbeing is essential for coaches and sport staff to detect trends that may progress towards negative wellbeing and poor performance outcomes (Saw et al., 2016). 91% of high performance facilities or clubs report using an athlete self-report measure (ASRM), making it one of the most commonly used methods of monitoring performance – they offer in depth detail of the athlete and their wellbeing/performance and they are highly cost effective (Saw et al., 2015). Other methods of monitoring include heart rate variability (HRV), blood lactate, urine specific gravity (USG) as well as GPS (Kellmann et al., 2010)

In order to invoke a physical adaptation, training load should be progressed over time but at a level that is maintainable by the athlete, and that is above the normal level of habitual state (Bell & Ingle, 2013). It is this progressive overload that must be monitored to ensure that overreaching is done in a gradual manner and overtraining is not invoked. Limitations in an athlete’s ability to perform at high standards is the capacity to endure high training loads/volumes without breakdown or maladaptation. Monitoring this load and ensuring the best practices for rest and recovery are paramount to prevent overtraining (Bell & Ingle, 2013).

Ineffective monitoring can illicit the same effects that it is trying to avoid – increased load being placed on the athlete to reach a benchmark (during performance testing) and or psychologically fatiguing (if using ASRM). An issue that may arise with chronic over monitoring can be the lack of adherence to the monitoring program and this will skew results (Saw et al., 2015). Monitoring, as defined by Halson (2014) needs to be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.

Athletes who have not been exposed to high loads of exercise due to under-training/over-recovering are more likely to be injured than an athlete who has been exposed to that level of stimulus. In a study by Blanch & Gabbett (2015) changes in the acute: chronic workload for an athlete had a high (R2=0.53) correlation with injury incidence – this purports that if an athlete is over-monitored and under-trained, they are more likely to become injured when that workload is changed. Optimal performance is therefore a balancing act between how well the athlete is handling the training load and their current acute: chronic workload for that training period.

Blanch, P., & Gabbett, T. J. (2016). Has the athlete trained enough to return to play safely? the acute:Chronic workload ratio permits clinicians to quantify a player's risk of subsequent injury. British Journal of Sports Medicine, 50(8), 471-475. doi:10.1136/bjsports-2015-095445

Bell, L. M., & Ingle, L. (2013). Psycho-physiological markers of overreaching and overtraining in endurance sports: A review of the evidence. Medicina Sportiva, 17(2), 81. doi:10.5604/17342260.1055272

Halson, S. L. (2014). Monitoring training load to understand fatigue in athletes. Sports Medicine, 44(2), 139-47. Retrieved from http://ezproxy.ecu.edu.au/login?url=http://search.proquest.com/docview/1651929672?accountid=10675

Kellmann M. Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring. Scandinavian journal of medicine & science in sports 20 Suppl 2: 95-102, 2010

Saw, A. E., Main, L. C., & Gastin, P. B. (2015). Role of a self-report measure in athlete preparation. Journal of Strength and Conditioning Research / National Strength & Conditioning Association, 29(3), 685-691. doi:http://dx.doi.org/10.1519/JSC.0000000000000698

Saw, A. E., Main, L. C., & Gastin, P. B. (2016). Monitoring the athlete training response: Subjective self-reported measures trump commonly used objective measures: A systematic review. British Journal of Sports Medicine, 50(5), 281-291. doi:10.1136/bjsports-2015-094758


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