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©Journal of Sports Science and Medicine (2017) 16, 443-449 
http://www.jssm.org 
 
 
Received: 05 July 2017 / Accepted: 10 August 2017 / Published (online): 01 December 2017 
 
 
` 
 
 
Heart Rate Variability is a Moderating Factor in the Workload-Injury 
Relationship of Competitive CrossFitTM Athletes 
 
Sean Williams 1, Thomas Booton 1, Matthew Watson 1, Daniel Rowland 1 and Marco Altini 2 
1 Department for Health, University of Bath, Bath, United Kingdom; 2ACTLab, University of Passau, Germany 
 
 
 
Abstract 
Heart rate variability (HRV) is a popular tool for monitoring 
training adaptation and readiness in athletes, but it also has the 
potential to indicate early signs of somatic tissue overload prior 
to the onset of pain or fully developed injury. Therefore, the aim 
of this study was to investigate the interaction between HRV, 
workloads, and risk of overuse problems in competitive Cross-
Fit™ athletes. Daily resting HRV and workloads (duration × 
session-RPE) were recorded in six competitive CrossFit™ ath-
letes across a 16 week period. The Oslo Sports Trauma Research 
Center Overuse Injury Questionnaire was distributed weekly by 
e-mail. Acute-to-chronic workload ratios (ACWR) and the 
rolling 7-day average of the natural logarithm of the square root 
of the mean sum of the squared differences between R–R inter-
vals (Ln rMSSDweek) were parsed into tertiles (low, moder-
ate/normal, and high) based on within-individual z-scores. The 
interaction between Ln rMSSDweek and ACWR on overuse 
injury risk in the subsequent week was assessed using a general-
ized linear mixed-effects model and magnitude-based infer-
ences. The risk of overuse problems was substantially increased 
when a ‘low’ Ln rMSSDweek was seen in combination with a 
‘high’ ACWR (relative risk [RR]: 2.61, 90% CI: 1.38 – 4.93). In 
contrast, high ACWRs were well-tolerated when Ln rMSSDweek 
remained ‘normal’ or was ‘high’. Monitoring HRV trends 
alongside workloads may provide useful information on an 
athlete’s emerging global pattern to loading. HRV monitoring 
may therefore be used by practitioners to adjust and individual-
ise training load prescriptions, in order to minimise overuse 
injury risk. 
 
Key words: Cardiac parasympathetic function, monitoring, 
training load. 
 
 
 
Introduction 
 
Overuse injuries occur due to repetitive submaximal load-
ing of the musculoskeletal system when rest is not ade-
quate to allow for structural adaptation to take place 
(DiFiori et al., 2014). The prevalence and negative impact 
of overuse injuries in competitive sports (Clarsen et al., 
2013) highlights the need for monitoring systems that can 
accurately reflect athletes’ evolving adaptations to train-
ing stimuli (Gisselman et al., 2016). Heart rate variability 
(HRV) is a popular tool for monitoring wellness and 
training adaptation in athletes (Bellenger et al., 2016). 
HRV involves measurement of the variation between 
individual heart beats across consecutive cardiac cycles, 
and this variation can provide an estimate of a person’s 
autonomic nervous system (ANS) activity (Malik, 1996). 
The emergence of smartphone applications and technolo-
gies has dramatically increased the accessibility of HRV 
measurement, such that it can now be recorded accurately 
using only a smartphone device (Plews et al., 2017). 
The ANS plays a dynamic role in the regulation of 
pain, inflammation and tissue repair (Ackermann et al., 
2016). Thus, some authors have postulated that monitor-
ing HRV, as an indirect measurement of ANS homeosta-
sis, has the potential to indicate early signs of somatic 
tissue overload prior to the onset of pain or fully devel-
oped injury (Gisselman et al., 2016). It is hypothesised 
that, relative to each athlete’s baseline HRV measure-
ments, imbalances in the parasympathetic and sympathet-
ic nervous systems may indicate an athlete is in a state of 
ongoing repair and recovery versus an athlete who is 
adapting positively to training load (Gisselman et al., 
2016). HRV measurements may therefore be used to 
improve our understanding of the mediators and modera-
tors in the workload-injury relationship (Windt et al., 
2017). 
CrossFit™ is a strength and conditioning pro-
gramme promoted as both an exercise methodology for 
the general population, and as the ‘sport of fitness’ for 
competitive athletes. Whilst concerns have been raised by 
some regarding the potential for disproportionate muscu-
loskeletal injury risk in extreme conditioning programmes 
such as CrossFit™ (Bergeron et al., 2011), initial injury 
epidemiology studies have reported the injury incidence 
rate in CrossFit™ training to be relatively low (2.1 – 3.1 
per 1000 training hours), and comparable to other forms 
of recreational fitness activities (Hak et al., 2013; 
Montalvo et al., 2017; Moran et al., 2017; Weisenthal et 
al., 2014). However, the methods used for injury registra-
tion in these studies are likely to have substantially under-
estimated the true burden of overuse injuries (defined as 
those without a specific, identifiable event responsible for 
their occurrence) due to a reliance on time-loss injury 
definitions (Clarsen et al., 2013). Overuse injuries are 
thought to be the predominant injury type in sports that 
involve high volumes of repetitive movement patterns, 
and/or high training loads (Clarsen et al., 2013); both of 
these factors are likely to be prevalent in CrossFit™ train-
ing, especially for competitive athletes who report signifi-
cantly greater training hours than non-competitors 
(Montalvo et al., 2017). 
At present, there is a paucity of research pertaining 
to competitive CrossFit™ athletes, despite the rapidly 
growing popularity of the sport. The number of athletes 
available for research studies from this elite population is 
inevitably small, which may increase the likelihood of 
making type II errors (whereby a practically important 
effect remains undetected through null hypothesis signifi-
Research article 
HRV and injury in CrossFitTM 
 
 
 
444 
cance testing). However, the use of magnitude-based 
inferences to determine the practical importance of out-
comes can mitigate this issue, as sample sizes approxi-
mately one-third those of null hypothesis significance 
testing are required (Batterham and Hopkins, 2006). 
Accordingly, the aim of this study was to investigate the 
interaction between HRV, workloads, and risk of overuse 
problems in competitive CrossFit™ athletes. 
 
Methods 
 
Subjects 
Six (three males, three females) competitive CrossFit™ 
athletes from one CrossFit™ training facility participated 
in this study and provided written consent prior to data 
collection. ‘Competitive’ was defined as training for the 
purpose of competing in organised CrossFit™ competi-
tions. The descriptive characteristics of the six competi-
tive CrossFit™ athletes at baseline are shown in Table 1. 
Two athletes (one male, one female) finished in the top 40 
of the ‘CrossFit™ Open’ in Europe (out of 38,238 and 
20,908 male and female competitors, respectively), and 
qualified for the ‘CrossFit™ Regionals’ competition. Of 
the remaining athletes, three finished the ‘CrossFit™ 
Open’ in the >95th percentile in Europe, whilst the re-
maining athlete was in the 85th percentile. The study was 
conducted in accordance with the principles of the Decla-
ration of Helsinki (World Medical Association, 2013) and 
a local university research ethics committee provided 
ethical approval. 
 
Table 1. Descriptive characteristics (mean ± SD) of competi-
tive CrossFit™ athletes at baseline. Data are means (±SD). 
 Male athletes (n=3) 
 Female 
 athletes (n=3) 
Age (years) 26 (4) 27 (2 
Height (m) 1.83 (.06) 1.67 (.10) 
Mass (kg) 88 (2) 67 (9) 
VO2 Max (ml/min/kg) 50 (1) 48 (3) 
Training