HRV Monitoring in a Team Setting: The Research

Though my original interest in HRV monitoring was for personal usage with my powerlifting training (and still is), I have become much more interested in its application with my athletes. In July, I wrote a post discussing some of the research and my thoughts on HRV in a team setting. I’ve come across some more great research that pertains to HRV monitoring in team settings and would like to share some thoughts on the topic.

Below is a  list of questions I’d like to address:

  • How effective is HRV monitoring in a team setting really?
  • What difference is there, if any, when monitoring HRV in elite vs. sub-elite athletes?
  • How practical is HRV monitoring in a team setting?
  • Can we create favorable autonomic profiles in athletes prior to intensive training blocks to improve global (all players) responsiveness to training? (to avoid injury, overtraining, etc)
  • How can we apply research that used frequency domain measures (HF, LF, HF/LF) with mobile apps/devices like ithlete and Bioforce that use RMSSD, a time domain measure of parasympathetic tone?

Keep in mind that I do not train elite athletes and therefore much of what I discuss is based on my interpretations of the research, discussions I’ve had with others and some theory. I certainly am not capable of providing answers to any of the above question.

First, I’d like to present brief summaries of the research I’ve read on the topic. I’ve only included studies that used HRV to monitor fatigue, training load, etc. At this time I’m not including studies using HRV during exercise, or post-exercise.

In some cases I could not get access to the full-text which you will see noted in the respective tables. Please enlighten me of any research on this topic I may have not included. I apologize for the poor presentation of the table’s below. I originally had all of this in a more reader friendly format in Word but for some reason it does not transfer over to wordpress very well.

Author Ke-Tien (2012)
Sport Male, National Level Rugby (n=24)
Aim To verify biological and psychological stress markers during strenuous cardiovascular endurance training periodization, using Profile of Mood States questionnaires, HRV & blood urine nitrogen as the criteria measurements.
Main Findings HRV correlated to profile of mood states survey and blood-urnine nitrogen in elite male national rugby players (n=24).
HRV Analysis Non-daily, Frequency Domain
Author Edmonds et al. (2012)
Sport Male, Elite Youth Rugby (n=9)
Aim To investigate the influence of weekly training & a competitive game on HRV in elite youth rugby league players, & to identify the importance of HRV as a monitoring tool for Rugby League player preparation.
Main Findings Prior to a match, elite youth, players exhibited a significant reduction in HRV that was sustained for at least 24 hours post-game. This withdrawal of parasympathetic &/or increased sympathetic control of HR possibly may result from pre-match anxiety as well as the physical demands of the game. Strong relationships between HRV and training load at Pre-2 indicate that early monitoring may assist in identifying training workloads for the upcoming week.
HRV Analysis Daily, Time & Frequency Domain
Author Oliveira et al. (2012a)  – Abstract Only
Sport Male, Elite Futsal (n=11)
Aim The aim of this study was to determine the changes in physical performance and resting heart rate variability (HRV) in professional futsal players during the pre-season and in-season training periods.
Main Findings Players improved their RSA & Yo-Yo IR1 performance with concomitant improvements in HRV. These indices were maintained during the in-season period while RSAbest was improved & RSAdecrement impaired. Frequent monitoring of these performances and HRV indices may assist with identification of individual training adaptations and/or early signs of maladaption.
HRV Analysis Non-daily, Unknown
Author Vantinnen et al. (2007)
Sport Male, Elite Soccer (n=24)
Aim To introduce a method commonly used in Finnish sport to monitor the exercise intensity & changes in recovery state of players in team sports by examining their heart rate (HR/HRV) responses to training & relaxation stimulus.
Main Findings Individual differences do exist in practices & games. This would imply that coaches need to quantify each game or practice exercise intensity & recovery for each individual, in order to organize & optimally prepare an individual training plan for each athlete.
HRV Analysis Various over 3 weeks (daily, nocturnal, 24 hr), Time and Frequency Domain
Author Oliveira et al. (2012b) – Abstract Only
Sport Male, Caliber Unknown, Soccer (n=10
Aim The aim of this study was to analyze whether the heart rate variability (HRV), assessed at the beginning of a soccer preseason, reveals a correlation with the improvement of physical performance over this training period.
Main Findings There were significant improvements in Yo-Yo IR1 performance & in the 30-m sprint time. The qualitative analysis revealed that the differences in Yo-Yo IR1 performance were very likely positive, were almost certainly positive for the sprint, but were inconclusive for the vertical jump. There was a strong correlation between one parasympathetic index and the change in performance. The study showed a strong correlation between parasympathetic indices of HRV with the performance improvement in Yo-Yo IR1 in the athletes during pre-season.
HRV Analysis Non-daily, Unknown
Author Rodas, G. et al. (2011) – Abstract Only
Sport Elite, Field Hockey (n=? entire team)
Aim To determine the changes in HRV during the 2006 World Cup
Main Findings HRV decreases progressively & the values of the parameters related to parasympathetic system activity (RMSSD & HF) reduce, which are indicative of good psychic-physical adaptability to the workload. At the same time, the value of the parameters related to sympathetic system activity (LF and LF/HF) increases, suggesting an increase in fatigue, tiredness and poor adaptability in general. Consequently, the analysis of HRV may be a good marker for monitoring the psychic-physical state, cardiovascular adaptability during exercise & a possible state of physical overload in athletes participating in competitions.
HRV Analysis Day of competitions only – Time and Frequency Domain
Author Martin-Sanchez et al. (2011)
Sport Male Pro Soccer (n=12) & Age/Sex matched Amateur Soccer (n=9)
Aim To determine if an intensive preseason training program modifies the inflammatory status in professional soccer players and if this inflammatory profile may be associated with the physical state.
Main Findings A negative association between cardiac low frequency & the plasma content of alpha-1 antichymotrypsin isotype 4, & a positive association between cardiac low frequency & fibrinogen gamma-chain isotype 3 was found. Our results suggest that the cardiac functional state of soccer players may be correlated with these proteins. Pro soccer players showed a decreased content of circulating proteins associated with inflammation compared with those in recreational soccer players.
HRV Analysis Morning of analysis – Time and Frequency Domain
Author Cipryan et al. (2010)
Sport Male, Hockey Junior Level (n=8), Adult (N=10)
Aim To present inter-individual differences in the reaction of autonomic nervous system (ANS) activity to the same training program, and to thereby support the importance of individual training in team sports during the conditioning period.
Main Findings The SA HRV monitoring mostly revealed significant differences in the level of the ANS activity among the players. A number of junior & adult players were characterized by almost permanently high ANS activity whereas other players occurred below the ANS activity level of healthy individuals.  The training efficiency (overreaching and injury reduction) can be positively influenced by creating training groups of players with similar ANS activity.
HRV Analysis Non-daily – Frequency Domain
Author Cipryan et al. (2007)
Sport Male, U-18 National Level Hockey (n=4)
Aim To investigate the influence of regular sport training on the activity of the autonomicnervous system (ANS) and to disclose patterns of interrelations between them.
Main Findings The results demonstrated that the player with the highest average TS (total score)& the highest average PT(total power) also showed the most consistent results & objectively the best performance in sport. On the other hand, the player with the lowest average TS and the lowest average PT also obtained the lowest average mark in the coach’s evaluation of his sports performance. The tendency to progression of the ANS  activity was different for each subject. The self-reports health status survey, which was given before measurements were taken, did not correspond with the results of the SA HRV measurement.
HRV Analysis Non-daily, Frequency Domain
Author Hap et al. (2010)
Sport Male, High Level Volleyball (n=8)
Aim The goal of the work was to verify the possibility of volleyball playersʼ training load optimization during a one week training microcycle based on the longitudinal observation of dynamics of SA HRV complex indices.
Main Findings 2 Players had above average levels ANS activity indicating higher training loads could be tolerated.4 Players had low ANS activity (but not below average) showing evidence of some fatigue and adaptation. Training loads are appropriate.

2 Players had below average ANS activity and their training adaptability was reduced.

HRV Analysis Daily – Frequency Domain
Author Parrado et al. (2010) – Abstract Only
Sport Elite, Field Hockey (n=? entire team)
Aim The aim of the study was to examine the utility of perceived tiredness to predict cardiac autonomic response to overload among feld hockey players during the 2006 World Cup.
Main Findings Results showed a negative correlation between perceived tiredness scores & time domain indexes, & a positive correlation of perceived tiredness scores and the high frequency component ratio (LF/HF ratio) of heart rate variability. Anxiety did not influence the precompetitive cardiac response despite somatic anxiety’s correlation with sympathetic response (LF/HF ratio) & tiredness scores. Perceived tiredness predicted the autonomic cardiac response to competitive overload. Thus, the perceived tiredness assessment would be a good early marker of fatigue & overload states during competition
HRV Analysis Day of analysis, Frequency Domain
Author Mazon et al. (2011)
Sport Male, Volleyball (n=32)
Aim To investigate the effects of selective loads of periodization model (SLPM) on autonomic modulation of HRV and endogenous stress markers before and after a competition period in volleyball players.
Main Findings SLPM did not change the cardiac autonomic modulation of HRV, but promoted beneficial adaptations in athletes, including positive changes in the plasma concentration of the endogenous stress markers. The absence of changes in HRV indicates that there is no direct relationship between cardiac autonomic modulation & endogenous stress markers in the present study.
HRV Analysis Pre & Post Training Cycle, Frequency Domain
Author Di Fronso et al. (2012)  – Abstract On
Sport Male, Amateur Basketball (n=7)
Aim To investigate the relationship between Heart Rate Variability (HRV) and performance in players of a basketball team during playoffs.
Main Findings Findings of this study suggest that vagal activity, expressed by HF index of HRV, can be positively related to the athletes’ performance. In particular, higher values of HF index during the morning of the match were associated with higher levels of athletes’ performance during the game.
HRV Analysis Morning of Competitions – Frequency Domain
Author Dranitsin (2008)
Sport Elite Male (n=12) and Female (n=1) Rowers
Aim The aim of this study was to examine the simultaneous effect on HRV of acclimatization to a hot, humid environment and a transition of five time zones in elite junior rowers.
Main Findings Major physiological adaptation of HRV indices in the standing position during acclimatization to a humid, hot environment, with a transition across five time zones, occurs within the first 5 days in elite athletes before returning to baseline. Indices of heart rate variability in the supine position correlate with the length of high-intensity training sessions on the previous day.
HRV Analysis Daily, Time Domain
Author Iellamo et al. (2004)
Sport Elite Male Rowers (n=8)
Aim To test the hypothesis that training-induced variations in T-wave amplitude at higher training loads are paralleled by changes in HR spectral profile.
Main Findings From 50% to 100% of training load, there was a significant decrease in HRV and increase in sympathetic tone. As training reduced to 50% during the World Championships, HRV returned to base line and a return of autonomic indices to previous levels was seen. 
HRV Analysis Non-Daily – Frequency Domain

I’ll discuss my thoughts on the questions I listed above in my next post.

Please share any studies pertaining to HRV usage in a team setting that I may have missed in the comments below or e-mail me

I joined twitter recently too @andrew_flatt


Cipryan, L. & Stejskal, P. (2010) Individual training in team sports based on ANS activity assessments. Medicina Sportiva, 14(2):  56-62 Free Full-Text

Cipryan, L., Stejskal, P., Bartakova, O., Botek, M., Cipryanova, H., Jakubec, A., Petr, M., & Řehova, I. (2007)  Autonomic nervous system observation through the use of spectral analysis of heart rate variability in ice hockey players.  Acta Universitatis Palackianae Olomucensis. Gymnica, 37(4): 17-21. Free Full-Text

Di Fronso, S. et al. (2012) Relationship between performance and heart rate variability in amateur basketball players during playoffs. Journal for Sports Sciences & Health, 8 (Suppl 1):S1–S70 45

Dranitsin, O. (2008) The effect on heart rate variability of acclimatization to a humid, hot environment after a transition across five time zones in elite junior rowers. European Journal of Sport Science, 8(5): 251-258 Abstract

Edmonds, RC., Sinclair, WH., and Leicht, AS. (2012) Theeffect of weekly training and a game on heart rate variability in elite youth Rugby League players. Proceedings of the 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update. 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update Research to Practice , 19-21 April 2012, Gold Coast, QLD, Australia , p. 183. Abstract

Hap, P., Stejskal, P. & Jakubec, A. (2010) Volleyball players training intensity monitoring through the use of spectral analysis of HRV during a training microcycle. Acta Universitatis Palackianae Olomucensis. Gymnica, 41(3): 33-38 Free Full-Text

Iellamo, F., Pigozzi, F., Spataro, A., Lucini, D., & Pagani, M. (2004) T-wave and heart rate variability changes to assess training in world class athletes. Medicine & Science in Sports and Exercise, 36(8): 1342-1346. Abstract

Ke-Tien, Y.(2012) Effects of Cardiovascular Endurance Training Periodization on Aerobic performance and Stress Modulation in Rugby Athletes. Life Science Journal, 9(2): 1218-25. Full-Text

Martin-Sanchez, F. (2011) Functional status and inflammation after preseason training program in professional and recreational soccer players: a proteomic approach. Journal of Sports Science & Medicine, 10: 45-51 Free Full-Text

Mazon, J. et al. (2011) Effects of training periodization on cardiac autonomic modulation and endogenous stress markers in volleyball players. Scandinavian Journal of Medicine & Science in Sports, doi: 10.1111/j.1600-0838.2011.01357.x Free Full-Text

Oliveira, RS. et al. (2012a) Seasonal changes in physical performance and HRV in high level futsal players. International Journal of Sports Medicine. DOI: 10.1055/s-0032-1323720 Abstract

Oliveira, RS. et al. (2012b) The correlation between heart rate variability and improvement in soccer player’s physical performance. Brazilian Journal of Kinanthropometry, 14(6) Abstract

Parrado, E.  et al. (2010)Percieved tiredness and HRV in relation to overload during a field hockey world cup. Perceptual and Motor Skills, 110(3): 699-713 Abstract

Rodas, G. et al. (2011) Changes in HRV in field hockey players during the 2006 World Cup. Apunts Medicina de l’Esport, (46): 117-123 Abstract

Vantinnen, T. et al. (2007) Practical experiences from measuring exercise intensity and recovery state with HR monitoring in team sport. Symposium Proceedings 6th IACSS Calgary, Alberta. Full-Text


5 New HRV Studies

There’s plenty of great research being done on HRV and its application to sport’s training. I’ll do my best to keep you apprised of the latest findings by periodically compiling abstracts of relevant studies. Unfortunately, I don’t have access to many of these newer studies and therefore will reserve comments until I do. In the meantime, check out the abstracts of some of the most recent research on HRV and athletes.


Leti, T., & Veronique, AB. (2012) Interest of analyses of heart rate variability in the prevention of fatigue states in senior runners. Autonomic Neuroscience: Basic & Clinical, Ahead of print

Background The use of heart rate variability (HRV) in the management of sport training is a practice which tends to spread, especially in order to prevent the occurrence of fatigue states.

Objectives To estimate the HRV parameters obtained using a heart rate recording, according to different exercise impacts, and to make the link with the appearance of subjective fatigue.

Methods Ten senior runners, aged 51 ± 5 years, were each monitored over a period of 12 weeks in different conditions: (i) after a resting period, (ii) after a day with training, (iii) after a day of competition and (iv) after a rest day. They also completed three questionnaires, to assess fatigue (SFMS), profile of mood states (POMS) and quality of sleep.

Results The HRV indices (heart rate, LF (n.u.), HF (n.u.) and LF/HF) were significantly altered with the competitive impact, shifting toward a sympathetic predominance. After rest and recovery nights, the LF (n.u.) increased significantly with the competitive impact (62.1 ± 15.2 and 66.9 ± 11.6 vs. 76.0 ± 10.7; p<0.05 respectively) whereas the HF (n.u.) decreased significantly (37.9 ± 15.2 and 33.1 ± 11.6 vs. 24.0 ± 10.7; p<0.05 respectively). Positive correlations were found between fatigue and frequency domain indices and between fatigue and training impact.

Conclusion Autonomic nervous system modulation-fatigue relationships were significant, suggesting the potential use of HRV in follow-up and control of training. Furthermore, the addition of questionnaires constitutes complementary tool that allow to achieve a greater relevance and accuracy of the athletes’ fitness and results.


Edmonds, RC., Sinclair, WH., and Leicht, AS. (2012) The effect of weekly training and a game on heart rate variability in elite youth Rugby League players. Proceedings of the 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update. 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update Research to Practice , 19-21 April 2012, Gold Coast, QLD, Australia , p. 183.

Introduction: To date, the majority of research related to rugby league has investigated movement patterns, injury mechanisms and the effects of training workload and a game on player fatigue. Interest in monitoring player workloads and recovery has increased recently, with heart rate variability (HRV) proposed as an important monitoring tool in both individual and team sports [1, 2]. Due to the high physical demands associated with rugby league, monitoring alterations in cardiac autonomic control via HRV may lead to improved player management and enhanced performance. The aim of this study was to investigate the influence of weekly training and a competitive game on HRV in elite youth rugby league players, and to identify the importance of HRV as a monitoring tool for Rugby League player preparation.

Methods: Youth rugby league players (n=9) were monitored during supine rest (10 min) at 2 days prior to a game (Pre-2), day of the game (Game Day), and 1 (Post-1), 2 (Post-2) and 4 (Post-4) days following a game. Heart rate (HR) recordings were recorded via a chest strap transmitter with beat-by-beat intervals during the last 5 min of supine rest analysed for time domain, frequency domain (low frequency [LF], high frequency [HF]) and non-linear measures of HRV. Player daily training load was calculated from players’ rating of perceived exertion and session duration as previously described (Foster, 1998). Significant (p<0.05) differences in HRV over the monitoring days were identified via 1-way ANOVA and post-hoc pairwise comparisons with a Bonferroni correction or a Friedman’s test with a Conover post-hoc comparison, where appropriate. Relationships between HRV variables and training loads were identified using Spearman’s rank rho (ρ) correlation coefficients.

Results: All time domain and nonlinear measures of HRV were similar over the 5 monitoring days except for mean HR, which was significantly greater on Game Day and Post-1 compared to Pre-2 (73.0 ± 5.7 and 80.1 ± 8.1 vs. 64.9 ± 8.7 beats per minute). On Game Day, LF and the ratio between LF and HF were significantly increased and remained elevated until Post-2 (Figure 1). In contrast, HF was significantly reduced on Game day and remained low until Post-2 (Figure 1). A strong negative correlation was identified between mean HR and training load on Pre-2 (ρ = -0.783, p < 0.05) with a strong positive correlation identified between HF and training load on Pre-2 (ρ = 0.700, p < 0.05).

Conclusion/Discussion: Prior to a competitive game, elite youth, Rugby League players exhibited a significant reduction in HRV that was sustained for at least 24 hours post-game. This withdrawal of parasympathetic and/or increased sympathetic control of HR possibly may result from pre-match anxiety as well as the physical demands of the game. Strong relationships between HRV and training load at Pre-2 indicate that early monitoring may assist in identifying training workloads for the upcoming week. The current results support HRV as an important monitoring tool for managing training workload.


Plews, DJ., Laursen, PB., Kilding & Buchheit, M. (2012) Heart rate variability in elite triathletes, is variation in variability the key to effective training? A case comparison. European Journal of Applied Physiology, 112(11): 3729-41.

ABSTRACT: Measures of an athlete’s heart rate variability (HRV) have shown potential to be of use in the prescription of training. However, little data exists on elite athletes who are regularly exposed to high training loads. This case study monitored daily HRV in two elite triathletes (one male: 22 year, VO2max 72.5 ml kg min−1; one female: 20 year, VO2max 68.2 ml kg min−1) training 23 ± 2 h per week, over a 77-day period. During this period, one athlete performed poorly in a key triathlon event, was diagnosed as non-functionally over-reached (NFOR) and subsequently reactivated the dormant virus herpes zoster (shingles). The 7-day rolling average of the log-transformed square root of the mean sum of the squared differences between R–R intervals (Ln rMSSD), declined towards the day of triathlon event (slope = −0.17 ms/week; r 2 = −0.88) in the NFOR athlete, remaining stable in the control (slope = 0.01 ms/week; r 2 = 0.12). Furthermore, in the NFOR athlete, coefficient of variation of HRV (CV of Ln rMSSD 7-day rolling average) revealed large linear reductions towards NFOR (i.e., linear regression of HRV variables versus day number towards NFOR: −0.65%/week and r 2 = −0.48), while these variables remained stable for the control athlete (slope = 0.04%/week). These data suggest that trends in both absolute HRV values and day-to-day variations may be useful measurements indicative of the progression towards mal-adaptation or non-functional over-reaching.


Tian, Y., He, ZH., Zhao, JX., Tao, DL., Xu, KY., Earnest, CP. & McNaughton, LR. (2012) Heart rate variability threshold values for early-warning non-functional overreaching in elite women wrestlers. Journal of Strength and Conditioning Research, Ahead of print

ABSTRACT: Functional overreaching (FOR) represents intense training followed by a brief reduction in performance, then a rapid recovery (<2 wk) and performance super-compensation. Non-functional overreaching (NFOR) occurs when the reduced performance continues ≥ 3 wk. Heart rate variability (HRV) is a promising tool for detecting NFOR. In this study, we examined HRV thresholds in 34 elite women wrestlers (mean ± SD: age 23±3 yr; height 165.6±6 cm, weight 63±8 kg) for FOR/NFOR during training before 11 major competitions. Supine HRV was analyzed weekly at the same time of day using time and frequency domain methods. We observed that the time domain index, square root of the mean of the sum of the squares of differences between adjacent RR intervals (rMSSD, ms), denoting parasympathetic tone, showed those responding normally to training (82.76 ms, 95% CI 77.75, 87.78) to be significantly different to those showing a decrease (45.97 ms, 95% CI, 30.79, 61.14) or hyper-responsiveness (160.44 ms, 95% CI, 142.02, 178.85; all, P< 0.001). Similar results were observed for mixed sympathetic and parasympathetic signal standard deviation of the NN intervals (SDNN, ms): Normal (65.39; 95% CI, 62.49, 68.29), decrease (40.07; 95% CI, 29, 51.14), and hyper-response (115.00; 95% CI, 105.46, 124.54; all, P< 0.001) and synonymous frequency domain components. An examination of the 95% CI shows a narrow band surrounding a normal response compared to broader bands accompanying adverse responses. Thus, severe perturbations both above and below normal responses lasting >2 weeks indicated an athlete’s transition to NFOR and, hence, are useful for assessing possible overreaching/training.


Maior, AS., Carvalho, AR., Marques-Nesto, SR., Menezes, P., Soares, PP. & Nascimento, JH. (2012) Cardiac autonomic dysfunction in anabolic steroid users. Scandinavian Journal of Medicine & Science in Sports, Ahead of print


This study aimed to evaluate if androgenic-anabolic steroids (AAS) abuse may induce cardiac autonomic dysfunction in recreational trained subjects. Twenty-two men were volunteered for the study. The AAS group (n = 11) utilized AAS at mean dosage of 410 ± 78.6 mg/week. All of them were submitted to submaximal exercise testing using an Astrand-Rhyming protocol. Electrocardiogram (ECG) and respired gas analysis were monitored at rest, during, and post-effort. Mean values of VO(2) , VCO(2) , and V(E) were higher in AAS group only at rest. The heart rate variability variables were calculated from ECG using MATLAB-based algorithms. At rest, AAS group showed lower values of the standard deviation of R-R intervals, the proportion of adjacent R-R intervals differing by more than 50 ms (pNN50), the root mean square of successive differences (RMSSD), and the total, the low-frequency (LF) and the high-frequency (HF) spectral power, as compared to Control group. After submaximal exercise testing, pNN50, RMSSD, and HF were lower, and the LF/HF ratio was higher in AAS group when compared to control group. Thus, the use of supraphysiological doses of AAS seems to induce dysfunction in tonic cardiac autonomic regulation in recreational trained subjects.