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Introduction: A cluster of studies in the sport science literature employ interval training (alternating bouts of recovery and rest periods) interventions for the purpose of identifying optimal training intensities for endurance performance. There has been evidence to support the likelihood that among the most optimal training stimuli are two specific intensities: the velocity associated with the maximal rate of oxygen uptake (v 2max); and the intermediate velocity between v 2max and the velocity associated with the lactate threshold (vΔ50). It has not been shown to date, which of the two interval training intensities (v 2max or vΔ50) enhances performance and laboratory determined performance-related parameters the most, when applied in a complete yearly training cycle of endurance runners. Most studies have been too short to provide definitive answers. Aim of the study: The aim of the study was to compare the interval training intensities v 2max and vΔ50 in a complete yearly training cycle so as to generate evidence as to which of the two impacts performance and performance-related parameters the most, with the goal of providing new knowledge in sport science. Methods: 32 out of the 45 male runners recruited initially completed the whole duration of the study (mean ± SD: body mass 72.0±8.0 kg, body height 175±6 cm, body fat 9.9±3.9 %, 2max 53.6±6.2 ml/kg.min, age 34±12 years). Subjects underwent a 20-week aerobic base of preparatory training (at an intensity equivalent to a rate of perceived exertion (RPE) of 10.4 to 11.0) and anaerobic threshold training (at an intensity equivalent to an RPE of 14.5 to 15.0). No high intensity training was included. At the end of the aerobic phase the runners underwent a pre-test phase for the determination of vΔ50, v 2max, 2max, vLT4 (speed associated with a lactate concentration of 4 mmol/L), ECR (Energy Cost of Running) and Tmax (maximum time at v 2max) in the laboratory and 1500-m and 5000-m time trial (TT) times on the track. The subjects were randomly assigned into one of two groups before entering the 16-week interval training intervention phase. The only difference between the two groups was the intensity of the interval training. Group A (n = 15) was trained at a heart rate associated with vΔ50 (mean RPE 16.8 to 17.0) and Group B (n = 17) was trained at a heart rate associated with v 2max (mean RPE 18.6 to 18.7). At the end of the interval training phase the subjects underwent the post-test phase involving the same tests as during pre-testing. A 2X2 (time VS. interval training intensity) mixed model analysis of variance was used to test for significant differences between and within groups and the level of significance was set at p< 0.05. Results: Group A improved significantly (mean difference and Confidence Interval (CI)) in 1500-m TT (10.1 s, CI 5.6 to 14.7 s), in 5000-m TT (22.9 s, CI 9.6 to 36.3 s), in vΔ50 (-0.4 km/h, CI -0.8 to -0.1 km/h), in Tmax (-71 s, CI -113 to -28 s) and vLT4 (-0.5 km/h, CI -0.8 to -0.1 km/h). Group B improved significantly (mean difference and CI) in 1500-m TT (11.7 s, CI 7.5 to 15.9 s), in 5000-m TT (29.0 s, CI 16.5 to 41.5 s), in vΔ50 (-0.4 km/h, CI -0.7 to -0.1 km/h), in v 2max (-0.4 km/h, -0.7 to -0.01 km/h) in Tmax (-78 s, CI -114 to -42 s) and in ECR (0.013 ml/m/kg, CI 0.005 to 0.021 ml/m/kg). Regression analyses showed that v 2max and vΔ50, individually, accounted for the highest degree of variance in 1500-m TT times (77% and 69%, respectively) and 5000-m TT times (79% and 78%, respectively). During multiple regression analyses v 2max was likely to be the most important predictor in the regression models predicting 1500-m TT times and vΔ50 was the most important predictor in the regression models predicting 5000-m TT times. Conclusions: The interval training intensities v 2max and vΔ50 were significant in leading to endurance performance improvement as well as to improvement in some associated physiological parameters. The novel findings were that, a) it was demonstrated that vΔ50 was significant in inducing improvements in the 1500-m TT, b) that both v 2max and vΔ50 may be the most important predictors of 1500-m and 5000-m performance in regression analyses and that, c) v 2max and vΔ50 may, with a high degree of probability, be the most important predictor of 1500-m and 5000-m times, respectively, during multiple regression analyses. The evidence seems to weigh towards v 2max to be a slightly more optimal training stimulus than vΔ50, which also constitutes an important training intensity. Considering injury potential, repetitive stress on the athletes and optimal training it may be that a combination may be sensible.

Field hockey is a popular sport played worldwide. Due to the demands of the game, injuries are common, restricting participation. Injuries occur due to a single traumatic event or are due to repetitive loading. Injuries caused by repetitive loading, known as overuse injuries, have been linked to various measureable kinetic and kinematic variables. The magnitude, direction and distribution of the applied loads have all been identified as factors influencing the onset of an injury. Furthermore, footwear, surface and speed of locomotion have also been identified as factors which will influence injuries. Altering these variables could assist in reducing the prevalence of overuse injuries across a population of participants. The initial study within this research investigated the magnitude and direction of applied ground reaction forces to the alignment of the tibia. Testing different insole surfaces, a rougher surface was found to increase proprioception, identified through a significant difference in the alignment of the tibia to the resultant ground reaction force vector. The next investigation used an adapted plantar pressure measuring device to record peak pressures between the uppers of the foot and shoes during various sports specific movements. Levels of peak pressures were found to match those under the feet. This method of assessment is therefore recommended for testing footwear designs in the future. Whilst there is an established relationship between the Ground Reaction Force (GRF) and tibial acceleration, this study compared a variety of previously reported GRF characteristics such as loading rates, peak forces and time to peak forces, to tibial accelerations using a shank mounted accelerometer system developed for this research. This provided identification of key ground reaction force characteristics linked to impact shock, for assessment of the footwear. This study then assessed a set of different footwear typically used by field hockey participants. The influence of these shoes on GRFs, and in–shoe pressure was investigated during running and jogging. These shoes along with a new prototype of running shoe designed to encourage forefoot running, were also assessed for their influence on impact shock measured directly using the shank mounted accelerometer system. A custom made computer program was employed to analyse the data. This program could be used in future research and clinical assessment. The results of the footwear evaluation identified that moulded cleat designs with a lack of midsole cushioning exposed participants to injury causing loading of the musculoskeletal system and therefore were not recommended for use in field hockey participation. Furthermore, the prototype running shoes were adjudged to require pre-training and further assessment. The other shoes which included running, soccer and hockey specific footwear did not produce any significant differences across the population of participants. However it was found that individual assessment produced many differences between the shoes. These results demonstrated that the shoes can have a positive and negative effect for different individuals on kinetics linked to overuse injuries. It was concluded that individual assessment was needed for identification of the correct footwear choice.

Many authors have proposed that sprint and distance front crawl swimmers differ in their stroke characteristics, however little three-dimensional quantitative data is provided to support these assumptions. It is currently unknown whether sprint and distance swimmers exhibit distinct stroke characteristics when swimming at the same pace. There were two main purposes of this study: 1) to determine whether there are distinct kinematic and kinetic differences between sprint and distance front crawl swimmers, and 2) to investigate whether stroke characteristics of front crawl swimmers, in terms of kinematic and kinetic variables change with swimming speed. Fifteen male national/international front crawl swimmers (17.87 +/- 2.33yrs; 73.87 +/- 8.72kg; 183.02 +/- 6.84cm) volunteered to participate in this study. This sample was composed of seven sprint (SG) and eight distance (DG) swimmers. Each testing session required swimmers to perform four 25m sprints and one 400m max effort (front crawl), with no pacing strategy, in a randomised order. Each trial was performed through a 6.75m3 calibrated space and recorded by six gen-locked JVC KY32 CCD cameras (4 below and 2 above water) sampling at a frequency of 50 fields per second. All trials were processed using ‘APAS’ software to obtain 3D coordinate data. Anthropometric measures were quantified using the elliptical zone method. Both data sets were entered into a bespoke MATLAB program which output: average swim velocity (Vav), stroke length (SL), stroke frequency (SF), stroke index (SI), vertical and lateral displacement for each segment, shoulder and hip roll angle, and elbow joint angle variables (1st back, shoulder x, end back, hand exit and recovery elbow angle). Stroke phase (entry, pull, push and recovery) durations (%) were quantified at instants corresponding to percentiles of the stroke cycle. Centre of mass position data were obtained from the digitised 3D data using a 14 segment rigid link body model in conjunction with the body segment parameter data obtained by the elliptical zone method. Component whole body velocity (VCOMHor), acceleration (accCOM) and net force (forceCOM) were derived from the centre of mass position data. Variables were statistically analysed in SPSS v.14.0, using a General Linear Model, repeated measures analysis of variance. The results indicated that the groups differed (p<0.05) with respect to the duration of the pull phase, the occurrence of max left and right shoulder roll and the temporal sequencing of the shoulders and hips rolling at both sprint and distance pace. Other variables approached significance between the groups, particularly when distance swimming, such as the duration of the push phase (p=0.082), the Vav (p=0.071) and average VCOMHor (p=0.071). The stroke kinematic variables that changed between paces (p<0.05) were the duration of the entry, pull, push, hand exit and recovery phases; the elbow angle at the end back position and the push phase range; total shoulder and hip roll; the sum average vertical displacement of the foot; the time to max vertical and lateral displacement of the finger; the time at max right elbow extension; the average VCOMHor, Min VCOMHor and Max VCOMHor. The stroke kinetic variables that changed between paces (p<0.05) were the Min accCOM, Max accCOM, range of accCOM, min forceCOM and max forceCOM. Other variables approached significance between the paces such as the entry elbow angle (p=0.084), the max right elbow extension (p=0.056), the finger lateral range (p=0.067) and the time to max accCOM (p=0.079). The SG displayed shorter durations of the pull and push phases than the DG for both paces, which was linked to the faster horizontal velocity and/or vertical acceleration of the hand. The sequencing order of the shoulders and hips changed between groups and paces, which was speculated to be controlled by the magnitude of the leg-kick. The main changes between paces were the greater magnitude of elbow angle at both the end back position and the push phase range, which contributed to the adjustment of kinetic variables. SL, SF, SI, Vav and the duration of the all the stroke phases changed between sprint and distance pace in order to meet the physiological requirements of the race distance. The prolonged duration of the entry phase, when distance swimming, resulted in a delayed attainment of the catch position and maximum stroke depth. Moreover, the magnitude of shoulder and hip roll increased at distance compared to sprint pace, which in turn influenced the magnitude of average vertical and range of lateral displacement of the finger between paces. In conclusion, contrary to the literature, SG and DG differed only with respect to the duration of the pull and push stroke phases and the sequencing order of the shoulders and hips. All swimmers adjust the majority of kinematic and kinetic variables depending on the swim pace in order to optimise performance for that race distance.

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Since the seminal work of Schwartz and Barsky (1977) detailing the notion of a home advantage, whereby teams perform consistently better at home opposed to away, there has been a plethora of research dedicated to studying this phenomenon. Many explanations for the home advantage have been proposed, including crowd support, venue familiarity, travel, rules, referee bias, and more recently, the territorial and behavioural responses elicited by a home venue. Neave and Wolfson (2003) reported that testosterone levels in male football players increased significantly at home compared to away, with defenders' levels higher than midfielders and forwards. Ice hockey players' pre-game cortisol levels have also been shown to be significantly higher at home (Carré, Muir, Belanger & Putnam, 2006). This thesis has attempted to provide a clearer understanding of the home advantage in football through both hormonal and perceptual perspectives.

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The present thesis sought to investigate the potential relationship between the second to fourth finger ratio (2D:4D), as a somatic marker of prenatal testosterone exposure, and basic numerical skills in children and adults. Chapter 1 presents a basic overview of the nature and effects of sex steroids followed by a more comprehensive consideration of literature regarding the reported effects of prenatal testosterone (PT) on the brain and cognition. The chapter then more specifically considers the possible influence of PT on numerical and mathematical competencies. Experiment 1 attempted to replicate evidence for a relationship between 2D:4D and basic numerical skills in children. The results revealed only one significant correlation, namely a significant positive correlation between right hand 2D:4D and number comparison scores in females. Chapter 3 discussed research regarding the nature and characteristics of so called ‗core‘ numerical competencies. Experiments 2-4 then attempted to explore any relationship between 2D:4D and performance on tasks designed to assess such skills in adults. The results of all three studies revealed an association between 2D:4D and lateralization for the process of subitizing relative to a comparable control task. The nature of this observed effect however varied across the three experiments. Experiment 4 also identified significant positive correlations between left hand 2D:4D and counting reaction times in females and a series of two way interaction effects between 2D:4D and task (numerical vs. control) for subitizing, counting and number comparison performance. The revealed interactions predominantly suggested faster task reaction times/higher accuracy in high 2D:4D (low PT) participants as compared to low 2D:4D (high PT) participants on the numerical tasks and the opposite pattern of results (i.e. high 2D:4D associated with poorer performance) on the control tasks. Experiment 5 investigated the association between 2D:4D and core numerical skills in children. Significant correlations were observed between; left hand 2D:4D and subitizing reaction times to the left visual field in males (negative direction), right hand 2D:4D and subitizing reaction times the right visual field in females (positive direction) and left hand 2D:4D and subitizing percentage error scores to the right visual field in females (negative direction). A possible relationship between 2D:4D and lateralization for both subitizing and number comparison relative to control was also found. For both numerical tasks low 2D:4D participants showed a right visual field advantage and high 2D:4D participants showed a left visual field advantage while different patterns of results were shown on the control task. Experiment 6 re-considered the relationship between 2D:4D and basic and core numerical skills in children using a standardised assessment of numerical competencies (the Dyscalculia Screener). No significant correlations however between 2D:4D and performance were identified. Finally, experiment 7 re-examined evidence for a link between 2D:4D and Key Stage 1 Standardised Assessment Test (SAT) scores. While the findings did not replicate evidence for a direct link between 2D:4D and SAT numeracy scores the results did demonstrate a significant negative relationship between right hand 2D:4D minus left hand 2D:4D (Dr-1; higher scores thought to indicate lower exposure to PT) and SAT numeracy scores in females. Such findings may potentially suggest a facilitative influence of PT on numeracy in women. Overall, while a number of interesting findings were revealed, limited consistency was identified across the results of the experiments conducted in the present thesis. The findings therefore offer no concrete support for a possible association between 2D:4D and basic numerical skills in either children or adults. The final chapter summarises the findings of each experiment and considers the results in the context of previous literature. General limitations of the research and suggestions for future research are discussed.

One of the current interests of exercise physiologists is to understand the nature and control of fatigue related to physical activity to optimise athletic performance. Therefore, this research focuses on the mathematical modelling and analysis of the energy system pathways and the system control mechanisms to investigate the various human metabolic processes involved both at rest and during exercise. The first case study showed that the PCr utilisation was the highest energy contributor during sprint running, and the rate of ATP production for each anaerobic subsystem was similar for each athlete. The second study showed that the energy expenditure derived from the aerobic and anaerobic processes for different types of pacing were significantly different. The third study demonstrated the presence of the control mechanisms, and their characteristics as well as complexity differed significantly for any physiological organ system. The fourth study showed that the control mechanisms manifest themselves in specific ranges of frequency bands, and these influence athletic performance. The final study demonstrated a significant difference in both reaction time and accuracy of the responses to visual cues between the control and exercise-involved cognitive trials. Moreover, the difference in the EEG power ratio at specific regions of the brain; the difference in the ERP components’ amplitudes and latencies; and the difference in entropy of the EEG signals represented the physiological factors in explaining the poor cognitive performance of the participants following an exhaustive exercise bout. Therefore, by using mathematical modelling and analysis of the energy system pathways and the system control mechanisms responsible for homeostasis, this research has expanded the knowledge how performance is regulated during physical activity and together with the support of the existing biological control theories to explain the development of fatigue during physical activity.

Strength training using free weights is performed by athletes in many sports as a means of enhancing performance. However, there is a dearth of research investigating the acute impact of bouts of this form of strength training on muscle function, which closely mimics the athletes’ sport or event. High forces are produced during a rowing race and subsequently strength training forms an integral part of the overall training programme for rowers. However, there is little documented evidence regarding the strength and conditioning practices occurring in rowing. Therefore the aims of this thesis were to investigate and draw conclusions regarding the strength and conditioning practices occurring within British rowing and to evaluate the impact of typical bouts of strength training on muscle function in rowers. To investigate the strength and conditioning practices within British rowing a questionnaire was completed by 32 coaches and semi-structured interviews were undertaken with two coaches of elite rowers (study 1). Information from both sources indicated that rowers performed two to three strength training sessions per week, involving Olympic lifting and multi-joint free weight strength exercises, performed across multiple sets with low to moderate repetition ranges. Physical testing most commonly involved assessment of cardiovascular endurance, muscular power and strength. Twenty four hours of recovery were generally afforded between strength training and intensive rowing training while longer periods were permitted before rowing races (> 48 h). Prior to the intervention studies, the reproducibility of subsequently assessed measures was assessed using trained rowers (study 2). Typical error (%) was low for 2000 m mean power (2.4 %), and low to moderate for the assessments of strength and power (3.0-5.9 %). Measures of peak blood lactate (11.5 %), creatine kinase (21.0 %) and surface electromyography (11.1-44.8 %, across various sites) demonstrated greater variability similar to previous studies. For studies 3 and 4, trained rowers performed 250 m and 2000 m rowing tests respectively, alongside various measures of muscle function before and after an acute bout of free weight multi-joint strength training (ST). For both studies, increases in perceived muscle soreness and CK indicated that muscle damage was present after ST for 24-48 h. Maximal power generating ability was decreased in both studies as evidenced by decrements in the 250 m test, power strokes, and jump height. However, in study 4, 2000 m rowing time was unaffected, leading to the conclusion that the specific muscle function required for the power tests was affected through damage to type II muscle fibres. Findings from study 1 indicated that rowers commonly perform strength training three times per week; therefore study 5 investigated the impact of this weekly frequency of strength training on muscle function. Twenty four hours after three bouts of ST within a five day period, trained rowers experienced significant decreases in maximal voluntary contraction, jump height and power stroke tests as well as increases in CK and soreness; however as with study 4, 2000m performance was unaffected. Trends for decreases in peak lactate and anaerobic energy liberation (p < 0.10, Effect Size = 0.40-0.56) were present alongside significant increases in EMG at three sites during the post-ST 2000 m test. These findings suggest a decreased utilisation of the anaerobic capacity coupled with increased central motor drive suggesting a change in muscular recruitment patterns during the follow up 2000 m rowing test. It would appear that following extensive strength training, physiological processes were adapted during subsequent rowing exercise, to compensate for the loss in higher threshold muscle fibre function, in order to affect the same level of rowing performance achieved in the rested state. These findings might suggest that participants operated within a physiological reserve and/or that multiple-exercise-regulation-algorithms exist with which a similar exercise performance can be achieved.