Relationship Between Heart Rate Variability and Acute:Chronic Load Ratio Throughout a Season in NCAA D1 Men's Soccer Players

• Published in: Journal of strength and conditioning research 2021-04, Vol.35 (4), p.1103-1109
• Main Authors: Sekiguchi, Yasuki, Huggins, Robert A., Curtis, Ryan M., Benjamin, Courteney L., Adams, William M., Looney, David P., West, Chris A., Casa, Douglas J.
• Format: Article
• Language: English
• Subjects: Adult; Heart Rate; Humans; Male; Physical Conditioning, Human; Seasons; Soccer; Workload; Young Adult
• ISSN: 1064-8011; 1533-4287
• DOI: 10.1519/JSC.0000000000002853

ABSTRACTSekiguchi, Y, Huggins, RA, Curtis, RM, Benjamin, CL, Adams, WM, Looney, DP, West, CA, and Casa, DJ. Relationship between heart rate variability and acute:chronic load ratio throughout a season in NCAA D1 menʼs soccer players. J Strength Cond Res XX(X)000–000, 2018—The purpose of this study was twofold(a) to examine the relationship between heart rate variability (HRV) and acute:chronic workload ratio (ACWR)-based training load (TL) metrics and (b) to examine relationships across various A:C ratio-based TL metrics. Heart rate variability in 23 male college soccer players (mean ± SD; age, 21 ± 1 years; body mass, 80.3 ± 5.8 kg; height, 181.9 ± 6.5 cm; %body fat, 11.9 ± 2.0%; and V[Combining Dot Above]O2max, 51.9 ± 5.0 ml·kg·min) was measured at 5 time pointsweek(W)1, W3, W7, W12, and W14 during the 2015 NCAA menʼs soccer season. Heart rate variability was calculated from beat to beat intervals using a heart rate monitor. Players donned a global position satellite–enabled device that measured the following TL metricssession time (ST), Player Load (PL), PL·min, and total distance (TD). Acute:chronic workload ratio was calculated for each TL metricACWR-based ST (ACWRST), ACWR-based PL (ACWRPL), ACWR-based PL·min (ACWRPLM), and ACWR-based TD (ACWRTD)ACWR = week average TLs/mo average (30 ± 1 days) TLs. Relationships between HRV and ACWR-based each TL metric were evaluated using mixed effects models. Tukey pairwise comparisons were used to examine differences between types of ACWR-based TL metrics. An increase in ACWRST significantly reduced HRV throughout a season (−7.4 ± 3.6 m·s; p = 0.04). There were significant differences between ACWRPLM and ACWRST, ACWRPL and ACWRTD at W1, ACWRPLM and ACWRST at W3 (p < 0.05). In conclusion, ACWRST, ACWRPL, and ACWRTD were significantly different from ACWRPLM. ACWRST was found to significantly predict HRV; higher ACWRST was significantly associated with lower HRV. Therefore, tracking of the ACWR using ST may help to optimize athleteʼs physiological state throughout a season.