| Title | Relationship Between Heart Rate Variability and Acute:Chronic Load Ratio Throughout a Season in NCAA D1 Men\'s Soccer Players. | ||
| Author | Sekiguchi, Yasuki; Huggins, Robert A; Curtis, Ryan M; Benjamin, Courteney L; Adams, William M; Looney, David P; West, Chris A; Casa, Douglas J | ||
| Journal | J Strength Cond Res | Publication Year/Month | 2021-Apr |
| PMID | 30289866 | PMCID | -N/A- |
| Affiliation + expend | 1.Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, Connecticut. | ||
Sekiguchi, 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 men\'s soccer players. J Strength Cond Res 35(4): 1103-1109, 2021-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虈o2max, 51.9 +/- 5.0 ml.kg-1.min-1) was measured at 5 time points: week(W)1, W3, W7, W12, and W14 during the 2015 NCAA men\'s 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 metrics: session time (ST), Player Load (PL), PL.min-1, and total distance (TD). Acute:chronic workload ratio was calculated for each TL metric: ACWR-based ST (ACWRST), ACWR-based PL (ACWRPL), ACWR-based PL.min-1 (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-1; 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 athlete\'s physiological state throughout a season.