Start Of Preseason Research Articles

Accuracy of a non-exercise method using seismocardiography for the estimation of V̇O2peak in sub-elite football players.

A non-exercise method equation using seismocardiography for estimating V̇O2peak (SCG V̇O2peak) has previously been validated in healthy subjects. However, the performance of the SCG V̇O2peak within a trained population is unknown, and the ability of the model to detect changes over time is not well elucidated. Forty-seven sub-elite football players were tested at the start of pre-season (SPS) and 36 players completed a test after eight weeks at the end of the pre-season (EPS). Testing included an SCG V̇O2peak estimation at rest and a graded cardiopulmonary exercise test (CPET) on a treadmill for determination of V̇O2peak. Agreement between SCG V̇O2peak and CPET V̇O2peak showed a large underestimation at SPS (bias±95% CI: -9.9±1.8, 95% Limits of Agreement: 2.2 to -22.0mL·min-1kg-1). At EPS no interaction (p=0.3590) but a main effect of time (p<0.0001) and methods (p<0.0001) was observed between SCG and CPET V̇O2peak. No correlation in V̇O2peak changes was observed between SCG and CPET (r=-20.0, p=0.2484) but a fair agreement in classifying the correct directional change in V̇O2peak with the SCG method was found (Cohen's κ coefficient=0.28±0.25). Overall, the SCG V̇O2peak method lacks accuracy and despite being able to estimate group changes, it was incapable of detecting individual changes in V̇O2peak following a pre-season period in sub-elite football players. The SCG algorithm needs to be further adjusted and the accuracy and precision improved for the method to be applicable for use within a trained population.

The Quantification of Physical Performance and Internal Training Load in Youth Male Soccer Players During Preseason.

The monitoring of training loads and quantification of physical performance are common practices in youth soccer academies to support coaches in prescribing and programming training for individuals. The interaction between training load and physical performance is unknown during a preseason period in youth soccer players. The current study assessed changes in training load and physical assessments across a 4-week preseason period. The relationship between physical performance and match playing time in youth male soccer players was also investigated. The training loads of 25 professional youth academy male soccer players were monitored throughout a 4-week preseason period. Assessments of power, agility, speed, and aerobic capacity were undertaken in the first training session. Session ratings of perceived exertion (sRPE) and well-being questionnaires were collected during all training sessions and preseason matches. Playing time during subsequent competitive matches was recorded. T test and 30-m-sprint assessments, conducted on the first day of preseason, were predictors of sRPE throughout preseason (t test χ2/df = 2.895, poor adjustment; 30-m sprint χ2/df = 1.608, good adjustment). YoYo Test performance was related with changes in perceived fatigue (χ2/df = 0.534, very good adjustment). Faster players reported higher values of sRPE, and players with higher aerobic capacity reported higher levels of fatigue across preseason. Well-being, perceived fatigue and soreness, and sRPE decreased across preseason. Greater match durations were related to higher levels of fatigue during preseason (P < .05). The current study highlights the relationship between training load, physical assessments, and playing time. Coaches and practitioners can use physical test data at the start of preseason as an indication of players that report higher sRPE, perceived fatigue, and reduced well-being across preseason, supporting decisions around individualized training prescriptions.

Seasonal health tracking of Australian Football League Women’s athletes

ABSTRACT Background Studies evaluating the dietary intake of Australian Football League Women’s (AFLW) athletes are few and limited to the preseason. This prospective observational study aims to evaluate seasonal changes in dietary intake and health parameters of professional AFLW athletes. Methodology Dietary intake (3-day weighed food records), body composition (bioelectrical impedance analysis, skinfolds), physical performance (global positioning system, GPS), and iron status (fasted blood sample) were assessed in 19 athletes (24 ± 5 years, 170 ± 6 cm, 22.8 ± 2.1 kg/m2) at three timepoints: start of preseason, end of preseason, and end of competition season. Sociodemographic information, sports nutrition knowledge (SNK), and risk of low energy availability (LEA) questionnaires were completed at the start of preseason. Results Mean daily energy and carbohydrate (CHO) intakes were lower than recommendations across all seasons (p < 0.05). Mean daily CHO intake was highest at start of preseason (3.6 g/kg/day), decreased during preseason (3.1 g/day) and remained low during competition (3.2 g/day); >80% of players did not meet minimum recommendations at each timepoint (all, p < 0.05). The sum of seven skinfolds and fat mass (%) decreased during preseason (both, p < 0.05). Serum iron fell within recommended ranges for 95% of athletes at all timepoints. The total distance (m) and number of Very High Intensity (>21 km/h) efforts significantly increased across preseason and decreased during competition (all, p < 0.05). Nutrition knowledge was ‘poor’, and 42% of athletes were at risk of LEA. Conclusions AFLW athletes do not meet energy and carbohydrate requirements across the preseason and competition seasons, which may impact health and performance if deficits are sustained.

The effect of rugby training on indirect markers of gut permeability and gut damage in academy level rugby players

PurposeTo assess indirect markers of intestinal endothelial cell damage and permeability in academy rugby players in response to rugby training at the beginning and end of preseason.MethodsBlood and urinary measures (intestinal fatty acid binding protein and lactulose:rhamnose) as measures of gastrointestinal cell damage and permeability were taken at rest and after a standardised collision-based rugby training session in 19 elite male academy rugby players (age: 20 ± 1 years, backs: 89.3 ± 8.4 kg; forwards: 111.8 ± 7.6 kg) at the start of preseason. A subsample (n = 5) repeated the protocol after six weeks of preseason training. Gastrointestinal symptoms (GIS; range of thirteen standard symptoms), aerobic capacity (30–15 intermittent fitness test), and strength (1 repetition maximum) were also measured.ResultsFollowing the rugby training session at the start of preseason, there was an increase (median; interquartile range) in intestinal fatty acid binding protein (2140; 1260–2730 to 3245; 1985–5143 pg/ml, p = 0.003) and lactulose:rhamnose (0.31; 0.26–0.34 to 0.97; 0.82–1.07, p < 0.001). After six weeks of preseason training players physical qualities improved, and the same trends in blood and urinary measures were observed within the subsample. Overall, the frequency and severity of GIS were low and not correlated to markers of endothelial damage.ConclusionsRugby training resulted in increased intestinal endothelial cell damage and permeability compared to rest. A similar magnitude of effect was observed after six weeks of pre-season training. This was not related to the experience of GIS.

Extreme blood lactate rising after very short efforts in top-level track and field male sprinters

ABSTRACT Two top-level (10”04 and 10”13 in 100-m dash) and 2 sub-elite (10”97 and 11”44 in 100-m dash) male sprinters completed, after a standardised warm-up, various jump, sprint and weightlifting exercises in two consecutive days at the start of pre-season. Before and 30 s after the tests, the [La−] were measured with a portable lactate analyser. The top-level sprinters exhibited much larger [La−] than the sub-elite sprinters (< 5 mmol·L-1) after all the exercise tests. The maximum values recorded were 20.4 mmol·L-1 after the 20-m sprint tests for Athlete 1, and 22.4 mmol·L-1 after CMJ testing for Athlete 2. The greater Δ% were recorded after CMJ testing for Athlete 1 (from 1.9 to 13.6 mmol·L-1), and after the power clean test for Athlete 2 (from 1.4 to 17.6 mmol·L-1). These results suggest a different metabolic response to very short efforts (≤3 s) in top-level track and field sprinters. These findings reinforce the need to include lactate assessments, during training and evaluation sessions, to better understand the acute and chronic adaptations to training of sprinters of different levels.

Biomarkers Differ Between And Within Starters And Non-Starters Throughout A Collegiate Soccer Season

PURPOSE: To observe differences in blood biomarkers (oxygen (O2) transport, immune, cardiovascular (CV) health and hematology) between starters (S) and non-starters (NS) over a full NCAA Division 1 collegiate men’s soccer season. METHODS: Biomarkers (n = 30) related to O2 transport (n = 9), immune function (n = 12), and CV and lipid profiles (n = 9) were collected at the start of pre-season (PS), in-season at weeks (W)1, 4, 8 and 12 in soccer players (n = 20, mean ± SD; age = 21 ± 1, height = 180 ± 6 cm, body mass = 78.19 ± 6.3 kg, body fat = 12.0 ± 2.6%, VO2max = 51.5 ± 5.1 ml·kg-1·min-1). A 2 x 5 (group x time) repeated measures ANOVA was used to identify differences between S (n = 10) and NS (n = 10). In the presence of a significant interaction effect (p<0.05), post-hoc one-way ANOVAs and paired tests were used to identify group and time differences with uncorrected alpha level set at p<0.05. RESULTS: A significant interaction effect (group x time) was found for 9 biomarkers (hematocrit [HCT], hemoglobin [HGB], red blood cells [RBC], total cholesterol [Total Chol], LDL cholesterol [LDL], Chol:HDL ratio, non-HDL cholesterol [non-HDL], direct LDL [dLDL] and apolipoprotein B [ApoB]). S demonstrated significant increases in RBC (W1) and Chol:HDL (W8), while NS demonstrated significant increases in HCT and HGB (W4); Chol:HDL (W4, 12). Within-group significant differences were found between PS and W1 for NS (HCT, HGB, RBC, Total Chol, LDL, Chol:HD, Non-HDL, ApoB) and for S (Chol:HDL, non-HDL, dLDL). HCT, HGB, RBC, LDL, Non-HDL, Direct LDL and Apo B were different in NS from W1 to W4, while only Apo B was different in S. From PS to W12, Total Chol, LDL, and non-HDL were significantly different for NS while HCT, HGB, Chol:HDL, and non-HDL were different in S. CONCLUSIONS: Our findings indicate that there are differences between and within S and NS for many biomarkers related to O2 transport, immune, CV health and hematology throughout a collegiate men’s soccer season. Thus, future analyses should account for playing status as a covariate. From a clinical perspective, while all biomarkers were within normal reference ranges, sports medicine personnel should account for playing status and inter-individual differences when tracking or diagnosing athletes who demonstrate signs of clinical pathologies associated with these biomarkers.

Early Season Hormonal and Biochemical Changes in Division I Field Hockey Players: Is Fitness Protective?

Walker, AJ, McFadden, BA, Sanders, DJ, Bozzini, BN, Conway, SP, and Arent, SM. Early season hormonal and biochemical changes in Division I field hockey players: is fitness protective? J Strength Cond Res 34(4): 975-981, 2020-The purpose was to evaluate changes in hormonal and biochemical markers as a result of the accumulated stress of the initial 4-week training block in field hockey players. Women's Division I field hockey players (N = 22; Mage = 19.7 ± 1.1 years) performed testing before the start of preseason (A1) that included body composition (%BF), vertical jump, and V[Combining Dot Above]O2max. Blood draws were conducted at A1 to assess creatine kinase (CK), iron (Fe), hemoglobin (HGB), hematocrit (HCT), percent saturation (%sat), total cortisol (TCORT), free cortisol (FCORT), interleukin-6 (IL-6), sex hormone-binding globulin (SHBG), prolactin (PRL), vitamin D (vitD), and thyroxine (T3). Blood draws were repeated 4 weeks later (A2). Athletes were monitored during this training block, which included 2 weeks of preseason and the first 2 weeks of the season, using heart rate monitors to determine energy expenditure (Kcal) and training load. There were significant disruptions in TCORT, FCORT, T3, CK, Fe, and SHBG (p < 0.05) from A1 to A2. V[Combining Dot Above]O2max accounted for 31% (p < 0.05) of the variance in TCORT and %BF accounting for an additional 20.1% (p < 0.05). V[Combining Dot Above]O2max accounted for 32.7% (p < 0.05) of the variance in FCORT. %BF accounted for 48.9% (p < 0.05) of the variance in T3. Kcal was positively correlated with V[Combining Dot Above]O2max (p < 0.05) and negatively correlated with %BF (p < 0.05). Athletes with higher V[Combining Dot Above]O2max and lower %BF may be capable of a higher work output and therefore more likely to experience increased physiological disruptions during intense training. The high-volume nature of preseason and differences in athlete fitness capabilities require coaches to manage players at an individual level to maintain athlete readiness.

Monitoring Blood Biomarkers and Training Load Throughout a Collegiate Soccer Season.

Huggins, RA, Fortunati, AR, Curtis, RM, Looney, DP, West, CA, Lee, EC, Fragala, MS, Hall, ML, and Casa, DJ. Monitoring blood biomarkers and training load throughout a collegiate soccer season. J Strength Cond Res 33(11): 3065-3077, 2019-This observational study aimed to characterize the responses of a comprehensive panel of biomarkers, observed ranges, training load (TL) metrics, and performance throughout the collegiate soccer season (August-November). Biomarkers (n = 92) were collected before the start of pre-season (PS), in-season weeks (W)1, W4, W8, and W12 in NCAA Division I male soccer players (n = 20, mean ± SD; age = 21 ± 1 years, height = 180 ± 6 cm, body mass = 78.19 ± 6.3 kg, body fat = 12.0 ± 2.6%, VO2max 51.5 ± 5.1 ml·kg·min). Fitness tests were measured at PS, and W12 and TL was monitored daily. Changes in biomarkers and performance were calculated via separate repeated-measures analysis of variance. Despite similar fitness (p > 0.05), endocrine, muscle, inflammatory, and immune markers changed over time (p < 0.05). Total and free testosterone was lower in W1 vs. PS, whereas free cortisol remained unchanged at PS, W1, and W4 (>0.94 mg·dL). Oxygen transport and iron metabolism markers remained unchanged except for HCT (W1 vs. PS) and total iron binding capacity (W8-W12 vs. W1). Hepatic markers albumin, globulin, albumin:globulin, and total protein levels were elevated (p < 0.05) at W12 vs. W1, whereas aspartate aminotransferase and alanine aminotransferase levels were elevated at W1-W12 and W8-W12 vs. PS, respectively. Vitamin E, zinc, selenium, and calcium levels were elevated (p < 0.05) at W12 vs. W1, whereas Vitamin D was decreased (p < 0.05). Fatty acids and cardiovascular markers (omega-3 index, cholesterol:high-density lipoprotein [HDL], docosahexenoic acid, low-density lipoprotein [LDL], direct LDL, non-HDL, ApoB) were reduced at W1 vs. PS (p ≤ 0.05). Immune, lipid, and muscle damage biomarkers were frequently outside clinical reference ranges. Routine biomarker monitoring revealed subclinical and clinical changes, suggesting soccer-specific reference ranges. Biomarker monitoring may augment positive adaptation and reduce injuries from stressors incurred during soccer.

Biomarker Response to a Competitive Season in Division I Female Soccer Players.

Walker, AJ, McFadden, BA, Sanders, DJ, Rabideau, MM, Hofacker, ML, and Arent, SM. Biomarker response to a competitive season in Division I female soccer players. J Strength Cond Res 33(10): 2622-2628, 2019-The purpose of this study was to evaluate effects of training load (TL) on performance and biomarkers of health, performance, and recovery in Division I female soccer players throughout a competitive season. Subjects (N = 25, Mage = 20 ± 1.1 years) were monitored before the start of preseason and every 4-weeks thereafter (T1-T5). A battery of performance tests was administered before the start of preseason (P1) and end-of-season (P2), including body composition (percent body fat [%BF], fat free mass [FFM], and fat mass), vertical jump (VJ), and VO2max. Blood draws were conducted at every time point (T1-T5) to assess free and total cortisol (CORTF and CORTT), prolactin (PRL), T3, IL-6, creatine kinase (CK), sex-hormone binding globulin, omega-3 (n-3FA), vitamin-D (Vit-D), iron (Fe), hematocrit (HcT), ferritin (Fer), percent saturation (%Sat), and total iron-binding capacity (TIBC). Daily exercise energy expenditure (EEE) and TL were determined. There were significant declines in VO2max, VJ, weight, and %BF from P1-P2 (p < 0.05) with no significant differences in FFM. Training load and EEE significantly decreased from T1-T3 (p < 0.05). Significant increases were seen in CORTT, CORTF, PRL, T3, IL-6, CK, and TIBC throughout the season (p < 0.05). Significant decreases were seen in n-3FA, Fe, Fer, %Sat, and Hct throughout the season (p < 0.05). Female athletes experience significant physiological changes following high TL and EEE associated with preseason and appear to be further exacerbated by the cumulative effects of the season. Unique insights provided by biomarkers enable athletes and coaches to be cognizant of the physiological changes that are occurring throughout the season.

Hip adduction and abduction strength and adduction-to-abduction ratio changes across an Australian Football League season

ObjectivesPre-season hip strength testing only represents the athlete’s level of conditioning at that time point, and may change over an Australian Football (AF) season. This study aimed to examine if there are changes in hip adduction, abduction and the adduction-to-abduction ratio between preferred and non-preferred kicking legs throughout an AF season. The influence of training load and player characteristics was also examined. DesignCross-sectional repeated measures. Methods38 uninjured elite AF players were included. Maximal isometric hip adduction and abduction strength were measured at four time points: start of pre-season (T1), end of pre-season (T2), mid-season (T3) and post-season (T4) using a hand held dynamometer with external belt fixation. ResultsHip adduction strength and hip-adduction-to-abduction ratio were greater in T3 compared to T1 (adduction by 22.71N, p<0.001, ratio by 0.15N, p<0.001) and hip adduction and abduction were weaker in T4 compared to T1 (adduction by 18.6N, p=0.004, abduction by 24.67N, p<0.001). No differences were found between the preferred and non-preferred leg in adduction (p=0.409) or abduction (p=0.602) strength. There was an interaction between leg and time point for the adduction-to-abduction ratio; at T3 and T4, the ratio of the preferred kicking leg was significantly lower than the non-preferred kicking leg (T3 by 0.14N, p=0.020, T4 by 0.15N, p=0.019). Training load was not significantly associated with strength changes. ConclusionsHip strength does change over an AF season. Regular in-season hip strength testing should occur to more accurately reflect player condition compared to one pre-season measurement.

The Seasonal Variations in Anthropometric and Performance Characteristics of Elite Intercounty Gaelic Football Players.

Kelly, RA, and Collins, K. The seasonal variations in anthropometric and performance characteristics of elite inter county gaelic football players. J Strength Cond Res 32(12): 3475-3482, 2018-There is limited research assessing the anthropometric and performance variations in elite Gaelic football. The aim of this study was to assess the anthropometric and performance characteristics of an elite intercounty squad within a season. After ethical approval and informed consent, 26 participants were assessed at the start of preseason (November), after early in-season (January), and midseason (March). Measurements included stature, body mass, sum of 8 skinfold sites (ΣSkf8), estimated body fat percentage (bf%), squat jump (SJ) and countermovement jump (CMJ), 5-, 10-, and 20-m sprint times, upper body and lower-body strength (1 repetition maximum), and Yo-Yo intermittent recovery test 2 (Yo-Yo IR2). A multivariate analysis of variance was used to determine seasonal and positional variations. Anthropometric variations were observed with an overall increase in participants' body mass and a concomitant decrease in ΣSkf8 and bf% (-21.5%, p = 0.002, η = 0.15; -1.43%, p = 0.004, η = 0.13). Performance variations showed improvements in sprint time over 5-m (p = 0.001, η = 0.19) and 10-m (p = 0.008, η = 0.11), SJ (p = 0.013, η = 0.1), CMJ (p = 0.013, η = 0.1) height and Yo-Yo IR2 (p < 0.001, η = 0.34) noted from preseason to midseason. Significant anthropometric variations are observed between the preseason and early in-season; meanwhile, significant performance variations are observed between the preseason and midseason. Distinct positional variations are evident for both anthropometric and performance characteristics at all time points. Applied practitioners should consider these findings when implementing a seasonal training plan.

Quantifying Changes in Squat Jump Height Across a Season of Men's Collegiate Soccer.

Sams, ML, Sato, K, DeWeese, BH, Sayers, AL, and Stone, MH. Quantifying changes in squat jump height across a season of men's collegiate soccer. J Strength Cond Res 32(8): 2324-2330, 2018-The purposes of this study were to examine the effectiveness of an athlete monitoring program in managing athlete neuromuscular fatigue across a men's collegiate soccer season as measured by changes in squat jump (SJ) height and to compare possible changes with the session rating of perceived exertion (sRPE) training load (TL). Eighteen outfield Division I men's college soccer players performed SJ testing before each game of the fall season in addition to a baseline measurement at the start of preseason. The athletes provided sRPE values after all training sessions, weight-training, and games. Linear mixed modeling was used to compare changes in SJ height across the season with the baseline, and a correlation coefficient and single-lag cross-correlation coefficient were calculated between TL and changes in SJ height. No statistically significant decreases in SJ height occurred across the season, although a moderate practical decline occurred after the preseason (-1.6 cm, effect size = -0.70). The correlation between TL and changes in SJ height was statistically nonsignificant, whereas the cross-correlation was significant (r = 0.18, p = 0.48 and r = 0.55, p = 0.02, respectively). The athlete monitoring program was successful in managing the athletes' neuromuscular fatigue across the season as evidenced by the maintenance of SJ height and positive relationship between TL and changes in SJ height. Thus, SJ monitoring may serve as a useful fatigue monitoring tool for collegiate soccer athletes. Future study is needed, relating changes in vertical jump performance to other markers of athlete preparedness and performance.

Seasonal Changes in Soccer Players' Body Composition and Dietary Intake Practices.

Devlin, BL, Kingsley, M, Leveritt, MD, and Belski, R. Seasonal changes in soccer players' body composition and dietary intake practices. J Strength Cond Res 31(12): 3319-3326, 2017-The aims of this study were 2-fold: to determine seasonal changes in dietary intake and body composition in elite soccer players and to evaluate the influence of self-determined individual body composition goals on dietary intake and body composition. This longitudinal, observational study assessed body composition (total mass, fat-free soft tissue mass, and fat mass) using dual-energy x-ray absorptiometry and dietary intake (energy and macronutrients) via multiple-pass 24-hour recalls, at 4 time points over a competitive season in elite soccer players from one professional club in the Australian A-League competition. Self-reported body composition goals were also recorded. Eighteen elite male soccer players took part (25 ± 5 years, 180.5 ± 7.4 cm, 75.6 ± 6.5 kg). Majority (≥67%) reported the goal to maintain weight. Fat-free soft tissue mass increased from the start of preseason (55,278 ± 5,475 g) to the start of competitive season (56,784 ± 5,168 g; p < 0.001), and these gains were maintained until the end of the season. Fat mass decreased over the preseason period (10,072 ± 2,493 g to 8,712 ± 1,432 g; p < 0.001), but increased during the latter part of the competitive season. Dietary intake practices on training days were consistent over time and low compared with sport nutrition recommendations. The self-reported body composition goals did not strongly influence dietary intake practices or changes in body composition. This study has demonstrated that body composition changes over the course of a soccer season are subtle in elite soccer players despite relatively low self-reported intake of energy and carbohydrate.

The Influence of Training Age on the Annual Development of Physical Qualities Within Academy Rugby League Players.

Till, K, Darrall-Jones, J, Weakley, JJ, Roe, GA, and Jones, BL. The influence of training age on the annual development of physical qualities within academy rugby league players. J Strength Cond Res 31(8): 2110-2118, 2017-Previous research in academy rugby league players has evaluated the development of physical qualities according to chronological age. However, no study has considered the training age, defined as the number of formalized years of strength and conditioning training, of these players. Therefore, the purpose of this study was to present and compare the annual changes in physical qualities of academy rugby league players according to training age. Sixty-one academy players undertook a fitness testing assessment, including anthropometric (height, body mass, sum of 4 skinfolds) and physical (10 and 20 m sprint, 10m momentum, vertical jump, Yo-Yo intermittent recovery test level 1 [Yo-Yo IRTL1], one-repetition maximum [1RM] squat, bench press and prone row) measures at the start of preseason on 2 consecutive annual occasions. Players were categorized into one of 3 training age groups (i.e., 0, 1, or 2 years) and were analyzed using magnitude-based inferences. Almost certain, very likely or likely annual improvements were identified for body mass, 10m momentum, Yo-Yo IRTL1, vertical jump, and all strength measures for the 3 training age groups. When training age groups were compared, 1 year showed possibly or likely lower strength increases than 0 years training age. However, the 2 years training age group demonstrated possibly or likely increased strength changes compared with 1 year. These findings suggest that training age is an important consideration for strength and conditioning practitioners but it is likely to be a combination of chronological age, biological maturity, and training experience alongside dynamic interplayer variability that influences the physical development of academy rugby league players.

NORDIC HAMSTRING EXERCISE STRENGTH CHANGES OVER A SEASON IN ACADEMY FOOTBALLERS

BackgroundThe Nordic hamstring exercise (NHE) has been utilised within Hamstring Strain Injury prevention programmes. However, there is a concern amongst some that once a football season has commenced, there is...

The effect of low back pain on trunk muscle size/function and hip strength in elite football (soccer) players

ABSTRACTLow back pain (LBP) is a common problem in football (soccer) players. The effect of LBP on the trunk and hip muscles in this group is unknown. The relationship between LBP and trunk muscle size and function in football players across the preseason was examined. A secondary aim was to assess hip muscle strength. Twenty-five elite soccer players participated in the study, with assessments conducted on 23 players at both the start and end of the preseason. LBP was assessed with questionnaires and ultrasound imaging was used to assess size and function of trunk muscles at the start and end of preseason. Dynamometry was used to assess hip muscle strength at the start of the preseason. At the start of the preseason, 28% of players reported the presence of LBP and this was associated with reduced size of the multifidus, increased contraction of the transversus abdominis and multifidus muscles. LBP decreased across the preseason, and size of the multifidus muscle improved over the preseason. Ability to contract the abdominal and multifidus muscles did not alter across the preseason. Asymmetry in hip adductor and abductor muscle strength was found between players with and without LBP. Identifying modifiable factors in players with LBP may allow development of more targeted preseason rehabilitation programmes.

Biomarkers Changes In Collegiate Female Power-Endurance Athletes

Non-functional overreaching (NFO) and overtraining Syndrome (OTS) result in impaired performance. Using biomarkers, it may be possible to detect early indications of these before deteriorations occur. PURPOSE: Evaluate changes in predictive biomarkers of NFO & OTS in female collegiate power-endurance athletes during the season and relate these changes to preseason fitness. METHODS: Division I female soccer & field hockey athletes (N=53, Mweight = 64.5 ± 6.9 kg; M%BF = 23.9 ± 5.7%; MVO2MAX = 47.6 ± 5.0 ml/kg/min; MVJ = 54.5 ± 7.4) participated in preseason fitness testing. Tests included body composition, vertical jump (VJ), VO2MAX & ventilatory threshold (VT). Blood was drawn at the start of preseason and 8 weeks later at midseason. The athletes arrived for blood draws in the morning in a euhydrated, fasted condition. Markers included insulin (IN), IL6, creatine kinase (CK), cortisol (CORT), prolactin (PRL), T3 & T4. RESULTS: IN (7.1 ± 2.9 vs 5.0 ± 4.6 uIU/ml) and T4 (1.2 ± .2 vs 1.1 ± .1 ng/dl) significantly decreased (P<.05), while IL6 (1.2 ± .6 vs 1.6 ± 1.3 pg/ml), CORT (25.2 ± 11.3 vs 30.4 ± 11.9 ug/dl), and PRL (14.1 ± 7.9 vs 18.5 ± 9.2 ng/ml) significantly increased (P<.05). Additionally, there were trends for increased CK (116 ± 106 vs 152 ± 110 U/L, P = .061) and T3 (108 ± 23.9 vs 113 ± 24.2 ng/dl, P = .072). Correlations for fitness measures and changes in biomarkers revealed significant associations between VT and T4, r = .506, P<.05, and LBM and CORT, r = .454, P<.05. Regression analyses revealed VT, VJ, and VO2MAX predicted 14.3% of variability in CORT (P<.05), with the largest predictive ability attributed to VO2MAX alone (R2 = .14, P<.05). Fitness also accounted for a considerable (R2 = .29, P<.05) amount of the variability in PRL while %BF also predicted changes in PRL (R2 = .18, P<.05). In all cases, higher fitness was associated with greater changes in biomarkers. CONCLUSION: Intense training without adequate rest leads to increased muscle breakdown, inflammation and stress as the body enters a more catabolic state. This is met with elevated metabolism to expedite recovery. Fitter athletes likely play more and receive less rest, so early detection of NFO symptoms through biomarkers may be a particularly useful monitoring strategy. Sponsored by Quest Diagnostics

Effect of Mouthgaurd and Stick Use on Aerobic Capacity High School Field Hockey Athletes

Many sports require the use of a mouthguard (MG) and the constraint of carrying a stick during play. Previous research has shown that these two conditions individually cause decrements to athletic performance; however, no research has been conducted on the effect of the combination of these conditions. PURPOSE:To determine effects of chronic MG and stick use during field hockey (FH) specific training on aerobic capacity; and to determine effects of acute use of MG and stick on aerobic capacity regardless of training group. METHODS:38 healthy female FH players (15+2 yrs.) from a local competitive high school team completed the study. Participants were placed into one of two groups: experimental (completing all conditioning with MG and stick) or control (completing all conditioning without MG and stick) by stratified random sampling matched for team level (Freshman, Junior Varsity or Varsity) and initial beep test performance. The beep test is a 20m multistage test that involves running in time with pre-recorded beeps. FH-specific training was performed as prescribed by coaching staff, with testing performed at baseline (start of preseason), 6 weeks (end of preseason) and 12 weeks (end of competition). Participants performed two beep tests, one with a MG and stick (MG-STK) and one without a MG and stick (WOMG-STK) during each testing block (baseline, 6 weeks, 12 weeks). Tests were performed >48 hours apart and the effects of MG and stick use were analyzed using a 3-way ANOVA. RESULTS:No difference was found in aerobic capacity between the experimental and control groups (p>0.05). It was determined that performing a beep test with MG and stick resulted in reduced aerobic performance (WOMG-STK: 37.41+6.65 ml·kg-1·min-1 vs. MG-STK: 33.16+5.02 ml·kg-1·min-1; p<0.01). Further, it was found that FH-specific training altered aerobic performance across the 12 weeks (p<0.01). Aerobic performance increased from baseline to midpoint (p0.05) (PRE: 33.37+4.29 ml·kg-1·min-1; MID: 37.52+6.81 ml·kg-1·min-1; POST: 34.94+6.65 ml·kg-1·min-1). CONCLUSIONS:Aerobic capacity was not affected by chronic use of MG and stick during standard FH-specific training. The use of MG and stick during the performance of a beep test diminished aerobic capacity across the study period.

Changes In Markers Of Recovery, Readiness, And Nutritional Status In Division I Female Soccer Players Over The First Half Of The Competitive Season

Athletes strive for a competitive edge through proper management and monitoring of training. Biomarkers are emerging as a potential tool for optimally assessing player health, recovery, and readiness. PURPOSE: To evaluate changes in various biomarkers associated with breakdown, recovery, and nutritional status in female collegiate soccer players in the first half of a competitive season. METHODS: Division I female collegiate soccer players (N=29; Mage= 20 ±1.3 yrs; Mweight= 64.7 ± 6.3 kg; Mheight= 166.8 ± 7.2 cm; M%BF= 22.0 ± 3.9 %) participated in blood draws at the start of preseason (T1) the first quarter of the season (T2) and at the midpoint (T3). The athletes arrived fasted and euhydrated the morning after a game. Hematocrit (HCT), IL-6, creatine kinase (CK), total cortisol (CORT), iron (Fe), Vit-D, omega-3-6 ratio (OMG36), and prolactin (PRL) were assessed. All players were monitored for training load using the Polar Team2 System. RESULTS: There were significant changes in HCT, Fe, OMG36, CK, CORT, and PRL (P< .05) over the first half of the season. HCT, Fe, and OMG36 each decreased significantly from T1 to T2 (ΔHCT = -1.4 ± 0.4 %; ΔFe=-45.9 ± 12.9 mcg/dL, ΔOMG36 = -1.8 ± 0.6) and remained significantly lowered at T3, P<.05. CK increased from T1 to T2 (ΔCK = 112.3 ± 41.8 U/L, P<.05) before returning towards baseline by T3, while CORT increased from T1 to T3 (ΔCORT = 6.9 ± 1.0 mg/dL, P<.05). Both markers were above clinical norms in-season. PRL significantly increase from T1 to T3 (5.8 ± 1.5 ng/ml, P<.05). There were no changes in daily training load, though accumulated training load significantly decreased (P< .05) from T2 (3691.9 ± 187.8) to T3 (2566.9 ± 133.9). CONCLUSION: The significant increases in CK, CORT, and PRL are consistent with overreaching and indicate incomplete recovery, despite typical training loads. While monitoring training load is a useful tool to account for the daily sport demands, the biomarkers appear to provide critical additional information to account for cumulative strain and recovery. Based on the changes in Fe and OMG36, nutritional insufficiencies may be partly responsible for impaired recovery. These results are consistent with subjective observations in team performance and provide support for the inclusion of biomarkers in comprehensive athlete monitoring. Supported by Quest Diagnostics

Strength and Power Development in Professional Rugby Union Players Over a Training and Playing Season.

To investigate strength and power development in elite rugby players during the different phases of a professional season. Sixteen professional rugby union athletes from an English premiership team were monitored for measures of lower-body peak force, force at 50 ms, force at 100 ms (all isometric squat), and power (explosive hack squat). Athletes were assessed at the start of preseason (T1), postpreseason (T2), midway through the competitive season (T3), and at the end of the competitive season (T4). Effect-size (ES) statistics with magnitude-based inferences were calculated to interpret differences in physical performance between the different stages of the season. Very likely beneficial increases in force at 50 ms (+16%, ES = 0.75 ± 0.4) and 100 ms (+14%, ES = 0.63 ± 0.4) were observed between T1 and T2. A likely beneficial increase in power was observed between T2 and T3 (+4%, ES = 0.31 ± 0.2). Between T3 and T4, decreases in force at 50 ms (-6%, ES = -0.39 ± 0.3) and 100 ms (-9%, ES = -0.52 ± 0.4) occurred, while peak force and power were maintained. Over the full season (T1-T4) clear beneficial increases in all measures of strength and power were identified. Meaningful increases in strength and power can be achieved in professional English premiership rugby players over a full playing season. The greatest opportunity for strength and power development occurs during pre- to midseason phases, while these measures are maintained or decrease slightly during the latter stages of a season.