In sport, the role of testosterone (T) and cortisol (C) in regulating training adaptations has been presented as being anabolic and catabolic to protein metabolism, respectively (18). However, recent work (34–36) suggests that training changes in hormones may not relate to anabolism and, in line with this argument, we (8) have suggested that T may be permissive to adaptation but not necessarily dose-related especially at the lower levels of change seen across training. Nevertheless, recent literature has highlighted far more complex roles for T and C in regulating neuromuscular function and adaptions (8,27,33), which include rapid bioavailability and potent effects on various neuromuscular outputs (e.g., brain functional connectivity, intracellular signaling, behavior, and cognition) (8,27).
Testosterone is also an important stress hormone, and the T responses to a stress challenge can provide information on dominant behavior, as seen in animals in a social hierarchy (5). For example, winning, in human competition, is often accompanied by elevated T levels relative to losing (12,13,20). More importantly, transient changes in T appear to be involved in the learning of behaviors that can lead to winning in future contests and one's motivation to compete again (3,26,29,30). From this perspective, the monitoring of T responsiveness to a physical challenge could provide information on the likely outcomes of future sporting events, especially in those sports where dominance and related competitive behaviors are key factors in contributing to success.
Cortisol has also been linked to competitive behavior and performance (12,28,31), and the behavioral responses (and effects) of T might be influenced by the C effects on the androgen receptors in threatening situations (19), which can be likened to elite competition. To complicate matters, basal T might itself predict changes in C and subsequent behaviors after a victory or defeat in competition (25). The literature is still somewhat equivocal in this area, and this probably reflects the complexity of simulations and one-off samples as opposed to longitudinal sampling over time. Furthermore, much of this work has been conducted in nonathletic populations and laboratory-based simulated competition settings (3,25,26,29) and thus has little relevance for athletes and the elite sporting environment.
To our knowledge, no studies have used the T and C measures to predict the likely outcomes of real competition in a team sport several days later. The early detection of team readiness to compete (or the lack of it thereof) would advance the conditioning and management of athletes by allowing coaching staff to intervene before an actual event to produce a more favorable outcome in team sport. Therefore, this study assessed the salivary-free T and C measures across selected training workouts and their association to subsequent competition outcomes in professional rugby league players. We hypothesized that the workout responses of free T (absolute and relative changes) would be greater before winning games, relative to losses, when played several days later.
Experimental Approach to the Problem
There is currently little information on the use of T and C as measurement tools for identifying likely competition outcomes in team sport. In this study, the salivary-free T and C responses to training workouts were compared with the subsequent outcomes of professional rugby league games. In terms of game-day outcomes, the first was wins and losses and the second involved the ranking of games (from 1 to 5) based on game-day performance, similar to that used previously (21). Saliva measures were chosen because they represent the ‘free' or biological active hormone, while being noninvasive and stress-free to collect (1,16). All testing was performed under normal training conditions to improve the internal validity of the study findings and their applications within elite sport.
Fourteen professional male rugby league players volunteered for this experiment, but only data from 13 players were retained for analysis because of a player transfer. Each player was considered healthy and injury-free at the time of this study. The participants had a mean age, body mass, height, and body fat of 23.3 ± 3.5 years, 94.6 ± 10.9 kg, 182.8 ± 5.1 cm, and 14.1 ± 2.5 %, respectively. They were training 5–6 d·wk−1 involving mainly skill and fitness conditioning, recovery and team training sessions, and played 1 to 2 games each week. The experiment was performed with University ethics approval, and each participant had a full explanation of the protocols, and they signed an informed consent before the study commenced.
Hormonal data were taken across 5 resistance-training workouts over a 7-week period at the start of the competitive season. These workouts formed part of a periodized training program aimed at maintaining power and strength. The monitored workouts were performed 2–4 days after each game, to ensure full recovery of the hormonal and neuromuscular systems (23,24), and 3–4 days before the next game. Where 2 games were played in a week, no testing was performed to facilitate player recovery. The training format started with a prehabilitation session, some basic power and strength tests, followed by full-body resistance exercises with appropriate loading protocols for maintaining strength and power. Weekly adjustments in these protocols were made to address the perceived needs of the team, as determined by the coaching staff after each game. Thus, although the intensity of training was relatively consistent (i.e., intensity range of 70–80% of maximal effort), the volume of load for the main exercises did vary (Table 1). The training workouts lasted approximately 1 hour.
The workouts were completed between 10 AM and 2 AM on each day to account for circadian variation (2,17). Trained exercise professionals attended each session and provided strong verbal encouragement with respect to player performance. Before the monitored sessions, or indeed any training session, a consistent consumption of breakfast and an attempt to get at least 7.5 hours of sleep on the previous night, was encouraged. Breakfast consumption included a combination of cereals, yoghurt, toast, fruit, fruit juice and water. The participants were asked to consume at least 750 ml of fluid in the preceding 2 hours (before testing) and had water available to them during each training workout. No food was taken 1.5–2 hours before and during the training workouts to eliminate the influence of food intake on salivary hormone concentrations (15).
The rugby league games that followed training workouts 1, 3, and 4 were won, and the games after workouts 2 and 5 were lost (Table 2). These games were played against Super League and Championship level teams at either home or other venues away. (Championship teams played in the Rugby League Challenge Cup, which can mean a Super League team is drawn against an amateur, semi-professional [Championship] team or full-time [Super League] team.) A simple rankings scale was used to quantify the competition outcomes based on the number of points scored (where 1 = biggest loss and 5 = biggest win) and the points differential (where 1 = biggest losing margin and 5 = biggest winning margin). The coaching staff also ranked team performance (where 1 = worst performance and 5 = best performance) based on several factors including: the opposition and venue, the abilities of the team and their work rate within each game, adherence to game plan, errors and penalties conceded, and the likely impact of previous game(s). The game-day rankings are presented in Table 2.
Saliva samples were taken 10 minutes before and 5 minutes after each workout. Approximately 2 ml of saliva was collected by passive drool into sterile containers and stored at −30° C until assay. After thawing and centrifugation (2,000 rpm × 10 minutes), the samples were analyzed in duplicate for free T and C concentrations using commercial kits (Salimetrics LLC, State College, PA, USA) and the manufacturers' guidelines to reduce any matrix effects. Extraction procedures are typically employed to eliminate any matrix effects, but pilot testing indicated that the T and C values from raw and extracted saliva samples are strongly related (r = 0.93–0.95). The minimum detection limit for the T assay was 6.1 pg·ml−1 with interassay coefficients of variation (CVs) of <12%. The C assay had a detection limit of 0.12 ng·ml−1 with interassay CV of <7%.
The hormonal responses to the training workouts were pooled across the competition outcomes (winning, losing), consistent with previous research (13). The pooled hormonal responses were subsequently assessed within each outcome and between these outcomes using dependent and independent t-tests, respectively. The bivariate relationships between the hormonal responses to each training workout and subsequent game outcome were tested using Pearson product moment correlations. The level of significance was set at p ≤ 0.05.
Hormone Concentrations Vs. Wins and Losses
A significant workout increase in free T concentrations (from pre to post) was noted before winning games (p < 0.01, Figure 1), but no workout changes were identified before a loss. Workout decreases in free C concentrations were observed before both winning and losing games (p < 0.001, Figure 2). For both T and C, there were no significant differences when either the presample or postsample (alone) values were compared across the different outcomes.
Hormone Responsiveness Vs. Wins and Losses
Significant relative increases in workout free T concentrations (Figure 3) were seen before winning games (30.9%, p < 0.001), but no T changes occurred before a loss (3.4%) and the observed differences were significant (p < 0.05). Decreases in the relative workout changes in free C concentrations were observed before both winning (−22.9, p < 0.01) and losing (−25.6, p < 0.05), but these responses were not significantly different (Figure 4).
Hormones Vs. Competition-Ranked Outcomes
The free T responses (%) to the individual training workouts were moderately related to the competition-ranked outcomes (Table 3), but these results were not significant. Weak and nonsignificant relationships were identified between the free C responses and the ranking outcomes (Table 3). We also found no significant correlations between preworkout or postworkout hormones and each of the game-ranked outcomes (data not presented).
The main finding of this study, consistent with our initial hypothesis, was that the pooled free T concentrations of professional rugby league players were elevated across training workouts that preceded winning games, but no hormonal changes occurred before the losses. The relative T responses to the training workouts also revealed a significant difference between the winning and losing outcomes, values being greater in the former.
Our recent work (unpublished finding) on international rugby union players supports these findings with greater exercise-induced changes in free T (%) occurring before each win (n = 3) across an international series and an international tournament, but with smaller or negative T changes observed before a loss (n = 4). Winning in a competition is often, but not always, accompanied by elevated T levels relative to losing (12,13,20), but to our knowledge, no other studies have used hormonal profiling around a physical challenge to predict the likelihood of a sporting outcome several days later. We do recognize one of the delimitations of our findings, in that it potentially reflects the individuals in one particular team, team culture, and the associated environment. Nevertheless, it is our suggestion that the T responses to selected training workouts might, in some manner, help to predict team readiness for some upcoming competitive situations.
Alternatively, transient increases in free T levels (which could be cumulative across numerous training sessions) might have a delayed effect on those adaptive systems directly influencing game-day performance, or these T patterns could simply reflect the recovery state of athletes from previous games. Studies have demonstrated that the willingness to engage in aggressive behaviors during a competitive task is positively correlated to individual changes in T (3). Likewise, the competition measures of T have correlated with aggressive behavior, motivation to win, and mood state in different athletic groups (20,28,31), all of which may contribute to physical performance in sport. However, correlations only suggest causation and notwithstanding the fact that the gross outcomes of any competition are multifactorial, especially in team sport.
Studies on untrained men suggest that physiologically elevated anabolic hormones do not enhance muscle size and strength (34–36). In accordance with these ideas, our recent work (8) supports a contention that although T might be permissive to hypertrophy, changes across a workout do not necessarily add to this. The present results suggest that there is a different, or perhaps an additional, mechanism underpinning the T effect linked to the concept of stress responsiveness and the notion that a positive stress response can predict, and possibly enhance, future resilience (5). Potentially, acute changes in T might be involved in the learning of behaviors that are conducive to winning or competing in future contests (3,26,29,30) and to physical performance during training workouts (9), or even to successful financial performance (e.g., stockbrokers) (6).
The workout changes in pooled free C concentrations were similar (decreasing) before the winning and losing games, which may simply reflect circadian variation (2,32) and the early morning testing of the study population. Despite this, the sampling protocols employed herein do not allow us to link daily changes in free C (or T) concentrations (2,17,32) to any of the study outcomes. This is an important consideration as the magnitude of the hormonal responses to exercise can vary with the time of day (11,32). As such, we are presenting a speculation based on a limited data set, but one we hope one may drive studies into this relatively new area. Future studies would no doubt benefit from more frequent sampling protocols across the waking day to identify other important patterns of hormonal change and their associations (if any) with the competitive outcomes of behavior and performance.
Salivary biomarkers were used in this study to circumvent some of the difficulties associated with blood collection in elite sport. Recent literature (4,14) has highlighted the advantages of saliva collection and analysis to ensure compliance in an elite group, as opposed to blood-derived hormonal measures. In fact, salivary T and C are more responsive (and thus more sensitive) to the physiological stressors of exercise than are the corresponding hormones in blood (10,16), which is relevant for this study. Moreover, the salivary T and C measures accurately reflect the biologically active free and the bioavailable hormone that is potentially available to target tissue (1,16).
The study findings are limited by the small number of training workouts and games monitored, and the number of athletes tested (n = 13), but this number is similar to other research on rugby league populations (22–24) and the selected group does represent a full playing team in this sport. We also recognize that load volume can influence the T and C responses to a training workout (7), but correlational analysis indicated that the hormonal changes were not significantly related to training load (r = −0.41 to 0.41, p > 0.05). Furthermore, different factors (e.g., behavior, neuromuscular) including hormones might have different weightings in their ability to predict an outcome, and this could change across training and competition blocks, or with different outcomes from previous games. More research is needed in elite sport to improve the validity, accuracy and applicability of any hormonal stress-test model to predict a competition outcome.
In conclusion, the free T responses to midweek training workouts showed some association with subsequent winning (being elevated) and losing (no change) during a limited number of games in professional rugby league. This suggests that T responsiveness to a physical challenge may help to predict team readiness to compete.
Our findings highlight the possible use of salivary biomarkers as tools for assessing team readiness to compete in professional rugby league. Specifically, elevations in free T levels across a midweek training workout would seem to be one, arguably, of many factors that reflect an optimal state for team performance during subsequent games, or possibly their recovery state. It would also be informative to assess the potential of other noninvasive markers (e.g., heart rate) as tools for predicting competition readiness in team sport. The early detection of team readiness or recovery state would provide a novel format for implementing training or management strategies to improve competition performance.
The authors acknowledge with gratitude the athletes and staff who contributed to this study. This project was partly supported by a grant from the Engineering and Physical Sciences Research Council, United Kingdom, and the UK Sports Council, as part of the Elite Sport Performance Research in Training with Pervasive Sensing Program (EP/H009744/1).
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Keywords:© 2013 National Strength and Conditioning Association
endocrine; sport; behavior; readiness; recovery