A Longitudinal Prospective Study: The Effect of Annual Seasonal Transition and Coaching Influence on Aerobic Capacity and Body Composition in Division I Female Soccer Players

This study assessed how seasonal transitions and coaching in uence a ect aerobic capacity (AC) and body composition across the annual training cycle (ATC). Eleven division 1 female soccer players were tested after ve predesignated time blocks (B1–B5): post-season 2016 (B1), nine-week transition (B2), spring season (B3), pre-season (B4), and post-season 2017 (B5). Height, weight, and body composition (fat-free mass (FFM)) were measured prior to a standardized 5 min treadmill running and dynamic movement warm up before a maximal AC test. Statistical analysis included a4 5repeated-measures analysis of variance (ANOVA) (dependent variable time) with the Fishers Least Signi cant Di erence (LSD) post-hoc test when relevant; data are presented as mean standard deviation, e ect size (ES), and percent change (%). The statistical analysis revealed that the ATC had a signi cant main e ect on AC and FFM (F3,42.81,p=0.001; 2=0.22). There were signi cant increases in AC across the transition period (B1–B2) with reduced training volume (D+12.9%,p=0.001; ES=0.50) while AC and FFM peaked after the spring season with directed concurrent training paired with adequate rest B1–B3 (D+16.4%,p<0.01; ES=0.81). AC decreased across the pre-season with indirect training (B3–B4) (D 7.0%,p=0.02; ES=0.50) and remained suppressed without change (p>0.05) across the competitive season (B4–B5). Rest, concurrent training, and directed training positively a ected AC, while indirect training and high training loads with little rest negatively a ected AC. Keywords: VO2max;

with directed concurrent training paired with adequate rest B1–B3 (D+16.4%,p<0.01; ES=0.81). AC decreased across the pre-season with indirect training (B3–B4) (D 7.0%,p=0.02; ES=0.50) and remained suppressed without change (p>0.05) across the competitive season (B4–B5). Rest, concurrent training, and directed training positively a ected AC, while indirect training and high training loads with little rest negatively a ected AC. Keywords: VO2max; periodization; detraining; training adherence; directed training; indirect coaching model; transition period 1. Introduction Seasonal training stress variation throughout the annual training cycle (ATC) is known to a ect aerobic capacity (AC) [1,2] and body composition [1,3–5]. Physiological adaptation is the result of exercise stress and then recovery, which varies according to training volume, intensity, frequency, and in uenced by seasonal transitions [6]. Cumulatively, training volume, intensity, and frequency make up total training load, which in uences adaptation. Training goals to a ect adaptation are known to di erentiate throughout the ATC with consideration of the competitive and o -season training [1–3,7], Sports2020,8, 107; doi:10.3390 /sports8080107 /journal/sports

Sports2020,8, 107 2 of 11 in addition to the transition period(s) [6,8]. Variation in training loads and goals throughout the ATC are typically divided into training periods and include but are not limited to the pre-competitive, competitive season, transition (detraining), and an o -season training period [5,6]. Training periods are further clari ed according to individualized and team sport demands and generally recognized as common practice in collegiate and professional sports. While soccer is a sport that prioritizes AC in combination with repeated short anaerobic sprints to maintain optimal performance [2–5,9], the literature has yet to agree how the training periods a ect AC across the ATC when accounting for team training dynamics, sport demands [1,3,5,7,9], and coaching strategies [10,11], which is further complicated by the lack of female presence in the current literature. Training type [6,10] within each training period has been shown to vary across the ATC depending on the time of year [6,12–14] in addition to intrinsic and extrinsic factors [6], e.g., weather, training cycle, and competitions, respectively. Coaches balance intrinsic and extrinsic limitations with yearly planning for peak physiological adaptation [3,5,6,12] while attempting to reduce risk of overtraining [6,8,12] during the competitive season. To accommodate these limitations, coaches typically include two variant styles: direct and indirect. Directed coaching uses direct oversight to facilitate interventions and increase adherence [10], while indirect is a passive method absent of direct contact with the coaching sta . Aerobic capacity is highly regarded as a determinant of soccer performance at elite levels [2,15–17] and is thought to very according to seasonal variation [2,6,8] despite evidence suggesting otherwise [3,5]. Therefore, to consider the impact of seasonal transition(s) with consideration of coaching in uence and more speci cally the variation in training periods (planned or not) throughout the ATC is necessary to optimize performance [6,8] and protect athletes from developing overtraining syndrome [18–20]. Within the ATC, training periods typically have a speci ed purpose/goal(s). For example, the transition period is de ned as a complete cessation or signi cant reduction in training load [6,8] and can range from 2 to 8 weeks [8].

(planned or not) throughout the ATC is necessary to optimize performance [6,8] and protect athletes from developing overtraining syndrome [18–20]. Within the ATC, training periods typically have a speci ed purpose/goal(s). For example, the transition period is de ned as a complete cessation or signi cant reduction in training load [6,8] and can range from 2 to 8 weeks [8]. During a transition period, extended rest has been shown to reduce AC [6,21] by as much as 20% in competitive endurance athletes [8] and with no di erences in whole-body FFM [1,15]. The decline in AC throughout the transition period [4,8] as a result of reduced training volume is thought to be attributed (in part) to a reduction in plasma volume, cardiac dimension [8,22], and ventilatory e ciency [8]. While the transition period is suggested to extend beyond 4 wks to recover from metabolic and tissue stress [6], the preparatory “season” and/or pre-competitive period [4,6,14] following the transition can include a sudden increase in training load (typical of the pre-competitive season) [6]. Without appropriate seasonal progression/planning, the sudden increase in training load could have deleterious e ects on how the players perform during the competitive season, speci cally decreased AC [4,6,23] and increased injury risk [6]. Furthermore, the large training loads the pre-season frequently includes is akin to concurrent training (CT) [6] and incorporates a combination of strength and endurance exercises [1,3,5,23]. The rapid increase in training load coaches employ during the pre-competitive season following the transition period (recovery) [4] paired with large-volume exercise such as CT can perpetuate physiological and psychological stresses. Most often, the broad accumulation of stress can facilitate increases in fatigue prior to the competitive season, leading to an inverse relationship with performance [6]. Accumulated training stress experienced during the pre-competitive season can overexert athletes from an overreached state (<2 weeks) [19,23] to an overtrained state (>2 weeks) [4,6] during the competitive season. Overtraining is de ned by excessive training stress paired with little rest between competitions and training [24,25], marked by a sustained reduction in performance beyond two weeks, and is typically accompanied by chronic

stress experienced during the pre-competitive season can overexert athletes from an overreached state (<2 weeks) [19,23] to an overtrained state (>2 weeks) [4,6] during the competitive season. Overtraining is de ned by excessive training stress paired with little rest between competitions and training [24,25], marked by a sustained reduction in performance beyond two weeks, and is typically accompanied by chronic fatigue, respiratory infections, and mood swings [4,6]. Frequent high-intensity competitions, practice, and variable o -season training can lead to accumulated stress, which alters physiological performance (both positive and negative have been observed) [3–5]. The continual stress that athletes experience while training and competing can create an imbalance in the homeostatic anabolic and catabolic muscular processes, which can negatively in uence performance [26]. Moreover, female athletes are 36% more likely to become overtrained compared to male athletes (26%) [27], further a ecting training and competition performance.

Sports2020,8, 107 3 of 11 Current research on trained adult soccer players (age 18) suggests that body composition uctuates [6] throughout the calendar year, while studies that include collegiate athlete populations indicate that the ATC does not have an e ect on body composition [3,5]. Considering body mass is included in relative AC measurement (mL kg 1 min 1 ) [2,8,15–17], changes in body composition can in uence AC [14,23] measurement and performance. Moreover, the primary oxidative tissue relevant to AC is fat-free mass (FFM) [15]. Therefore, increases in FFM from CT would likely increase AC [4,14,23]. Contrariwise, adipose tissue does not contribute to maximal oxygen consumption and therefore an inverse relationship exists between fat tissue and AC [15,28], further demonstrating the e ect of body composition on AC. Therefore, the aim of this study was to evaluate the e ect of seasonal transition, training stress, and coaching in uence throughout the ATC on AC with consideration of body composition in Division I female soccer players. 2. Materials and Methods 2.1. Exercise Design Using a repeated-measures design, this study investigated the e ect of seasonal transition throughout the ATC on AC and body composition. Aerobic capacity (mL kg 1 min 1 ), body weight (BW) in kilograms (kg), body fat percentage (%BF) expressed as a percent of body weight (%), and FFM (kg) were collected across ve predesignated seasonal transitions where training focus varied— post-season2016 (B1), transition (B2), spring season (B3), pre-season (B4), and post-season 2017 (B5)—as shown in Figure. Exercise testing occurred at the end of each separate season marked by time blocks (B1, B2, B3, B4, B5). Sample size was determined using an a priori power analysis with an e ect size of 0.68 from Miller et al. [3] and a power of 0.98. Potential subjects were excluded if they self-reported or had any diagnosed cardiovascular, metabolic, pulmonary disorders, pregnancy, or had experienced any orthopedic injuries preventing safe testing. This study was conducted according to the Declaration of Helsinki guidelines and all procedures were approved by the University Institutional Review Board. Twenty-two subjects who had completed a full

[3] and a power of 0.98. Potential subjects were excluded if they self-reported or had any diagnosed cardiovascular, metabolic, pulmonary disorders, pregnancy, or had experienced any orthopedic injuries preventing safe testing. This study was conducted according to the Declaration of Helsinki guidelines and all procedures were approved by the University Institutional Review Board. Twenty-two subjects who had completed a full National Collegiate Athletics Association (NCAA) Division 1 (D1) season prior to the study agreed to participate after providing informed written consent. Subjects completed a health history questionnaire and were informed of pre-test guidelines prior to each testing block which consisted of refraining from exercise for a minimum of 24 h, avoiding stimulants/depressants including ca eine for 12 h, and fasting for four hours before all testing blocks. Subject attrition included ve subjects who dropped from the study—three due to positional characteristics (goalies), and three due to injury and/or illness (n=11).Sports 2020, 8, x FOR PEER REVIEW 3 of 11 Current research on trained adult soccer players (age ≥ 18) suggests that body composition fluctuates [6] throughout the calendar year, while studies that include collegiate athlete populations indicate that the ATC does not have an effect on body composition [3,5]. Considering body mass is included in relative AC measurement (mL·kg −1 ·min −1 ) [2,8,15–17], changes in body composition can influence AC [14,23] measurement and performance. Moreover, the primary oxidative tissue relevant to AC is fat-free mass (FFM) [15]. Therefore, increases in FFM from CT would likely increase AC [4,14,23]. Contrariwise, adipose tissue does not contribute to maximal oxygen consumption and therefore an inverse relationship exists between fat tissue and AC [15,28], further demonstrating the effect of body composition on AC. Therefore, the aim of this study was to evaluate the effect of seasonal transition, training stress, and coaching influence throughout the ATC on AC with consideration of body composition in Division I female soccer players. 2. Materials and Methods 2.1. Exercise Design Using a repeated-measures design, this study investigated the effect of seasonal transition throughout the ATC on AC and body composition. Aerobic capacity (mL·kg −1 ·min −1 ), body

effect of seasonal transition, training stress, and coaching influence throughout the ATC on AC with consideration of body composition in Division I female soccer players. 2. Materials and Methods 2.1. Exercise Design Using a repeated-measures design, this study investigated the effect of seasonal transition throughout the ATC on AC and body composition. Aerobic capacity (mL·kg −1 ·min −1 ), body weight (BW) in kilograms (kg), body fat percentage (%BF) expressed as a percent of body weight (%), and FFM (kg) were collected across five predesignated seasonal transitions where training focus varied— post-season 2016 (B1), transition (B2), spring season (B3), pre-season (B4), and post-season 2017 (B5)— as shown in Figure 1. Exercise testing occurred at the end of each separate season marked by time blocks (B1, B2, B3, B4, B5). Sample size was determined using an a priori power analysis with an effect size of 0.68 from Miller et al. [3] and a power of 0.98. Potential subjects were excluded if they self-reported or had any diagnosed cardiovascular, metabolic, pulmonary disorders, pregnancy, or had experienced any orthopedic injuries preventing safe testing. This study was conducted according to the Declaration of Helsinki guidelines and all procedures were approved by the University Institutional Review Board. Twenty-two subjects who had completed a full National Collegiate Athletics Association (NCAA) Division 1 (D1) season prior to the study agreed to participate after providing informed written consent. Subjects completed a health history questionnaire and were informed of pre-test guidelines prior to each testing block which consisted of refraining from exercise for a minimum of 24 h, avoiding stimulants/depressants including caffeine for 12 h, and fasting for four hours before all testing blocks. Subject attrition included five subjects who dropped from the study—three due to positional characteristics (goalies), and three due to injury and/or illness (n = 11). Figure 1. Exercise design includes maximal aerobic capacity (AC) and body composition testing across all predesignated time blocks (B1–B5) throughout the annual training cycle (ATC). Seasonal transitions and training period focus are identified intermittently between testing blocks. Regulated coach communication periods are mandated by the Division I National Collegiate Athletics

and three due to injury and/or illness (n = 11). Figure 1. Exercise design includes maximal aerobic capacity (AC) and body composition testing across all predesignated time blocks (B1–B5) throughout the annual training cycle (ATC). Seasonal transitions and training period focus are identified intermittently between testing blocks. Regulated coach communication periods are mandated by the Division I National Collegiate Athletics Association compliance rulebook [29]. (CT) designates when concurrent training style was implemented during designated time blocks. Figure 1. Exercise design includes maximal aerobic capacity (AC) and body composition testing across all predesignated time blocks (B1–B5) throughout the annual training cycle (ATC). Seasonal transitions and training period focus are identi ed intermittently between testing blocks. Regulated coach communication periods are mandated by the Division I National Collegiate Athletics Association compliance rulebook [29]. (CT) designates when concurrent training style was implemented during designated time blocks.

Sports2020,8, 107 4 of 11 2.2. Subjects Eleven (n=11) Division I female soccer players (mean SD: 19.3 1.0 years; 164 6.4 cm; 60.1 5.4 kg ; 19.4 3.5% BF, 48.3 4.0 kg FFM, 43.3 3.3 mL/kg/min VO2max) were included in the study. All included subjects completed a series of graded exercise tests (GXTs) to assess AC along with body composition over ve predesignated time blocks (B1–B5). For each testing block, after con rmation of pre-test guideline adherence subjects completed a urine-based pregnancy test as pregnancy was an exclusion criterion to maximal testing [30]. Throughout the ATC, subjects arrived to the lab for each testing block, where height and weight were measured via an electric standiometer and a scale (Seca Corp., Chino, CA, USA). Body density was measured by a trained researcher using handheld skinfold calipers (Beta Technology, Santa Cruz, CA, USA) and the three site skin fold method: triceps, suprailiac, and thigh [30]. Body composition was then estimated (%BF) using the Brozek conversion equation [30,31]. 2.3. Aerobic Capacity Testing Prior to each exercise test, subjects were tted with a heart rate (HR) monitor (Polar Inc., Warminister, PA, USA) and completed a standardized dynamic warm up (high knees, butt kickers, and high bounds) prior to a 5 min self-selected warm up to acclimate to treadmill (Life Fitness Inc., Rosemont, IL, USA) running. Expired gases were measured (ADInstruments Inc., Sydney, Australia) along with HR and RPE at 1 min intervals. Heart rate was measured using a wireless signal integrated into the metabolic cart from a chest strap. Each treadmill GXT protocol was designed to begin with a brisk walk (1.6–1.8 m s 1 ). Each 1 min stage increased velocity by 0.22–0.44 m s 1 to ensure that volitional fatigue would occur within 8–12 min [32,33]. Standardized criteria for the determination of VO2maxalong with a 15 s running average as described by Robergs et al. 2010 [34] were used to determine VO2max. Each testing block repeated the above procedure across the ATC at the ve predesignated time blocks (B1–B5), as shown in Figure. 2.4. Speci ed Training Season Focus Each testing block

within 8–12 min [32,33]. Standardized criteria for the determination of VO2maxalong with a 15 s running average as described by Robergs et al. 2010 [34] were used to determine VO2max. Each testing block repeated the above procedure across the ATC at the ve predesignated time blocks (B1–B5), as shown in Figure. 2.4. Speci ed Training Season Focus Each testing block followed periodized training periods with pre-determined team training goals implemented by the coaching sta depicted in Figure. The transition period (B1–B2) totaled 10 weeks and immediately followed the 2016 competative season. Moreover, the transition period included an indirect training method (no direct coach oversight) with no speci ed exercise prescription and a NCAA regulated/limited coaching communication period [29]. The 12 week spring season (B2–B3) increased training volume, frequency, and intensity, which included regular bouts of directed (strength coach facilitated) CT ( 3 week) along with regular aerobic and velocity training that had a sport speci c focus. Fifty percent of the spring season consisted of an 8 h/week CT period and the remaining 50% 20 h CT weeks. The pre-season (B3–B4) was 15 weeks in length and employed an indirect training method (no direct coach oversight), where subjects were given a periodized CT program with speci ed aerobic, anaerobic, and resistance training exercises that included frequency, volume, and intensity prescriptions. Throughout the pre-season, subjects participated separately in “summer league play”, with periodic competitions that varied sample wide. The pre-season was also a NCAA-mandated period of limited coach communication [29] and therefore the potential for sample wide variation in training volume, intensity, and frequency was high. Lastly, the competative season (B4–B5) spanned 15 weeks, included a minimum of two NCAA collegiate competitions per week and ~four days of CT training/practice per week. 2.5. Statistical Analysis A 4 5 repeated-measures ANOVA was used to analyze dependent variables: AC (mL kg 1 min 1 ), FFM (kg), %BF (%), BM (kg) across ve time blocks (B1–B5) using Statistical Package for the Social Science (SPSS), Version 23 (IBM Corp., Armonk, NY, USA). Alpha level of signi cance was set

week. 2.5. Statistical Analysis A 4 5 repeated-measures ANOVA was used to analyze dependent variables: AC (mL kg 1 min 1 ), FFM (kg), %BF (%), BM (kg) across ve time blocks (B1–B5) using Statistical Package for the Social Science (SPSS), Version 23 (IBM Corp., Armonk, NY, USA). Alpha level of signi cance was set

The study evaluates the impact of seasonal transitions and coaching on aerobic capacity in female soccer players.