Zweite Studienarbeit Hochschule für Angewandte Psychologie Zürich, 2006.

Thesis (M.S.)--Wisconsin. / Includes bibliographical references (leaves 88-93).

Thesis (Ed. D.)--Indiana University of Pennsylvania, 2002. / Includes bibliographical references (leaves 201-210).

Thesis (Ph. D.)--Michigan State University, 2004. / Includes bibliographical references (leaves 121-129).

Thesis (Ph. D.)--Michigan State University, 2006. / Includes bibliographical references (leaves 194-204). Also available online (PDF file) by a subscription to the set or by purchasing the individual file.

Thesis (Ph. D.)--Michigan State University, 2006. / Includes bibliographical references (leaves 194-204).

Thesis (Ph. D.)--University of Ottawa, 2004. / Leaf 129 is upside-down. Includes bibliographical references (leaves 329-351).

Thesis (Ed.D.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / Bandura (1986,1997) asserts that a group's belief in its members' co-joint abilities, or its collective-efficacy, influences the degree to which that group seeks challenging goals, puts forth effort, and persists in the face of adversity. Group leaders serve important functions in the development of successful groups (Yalom, 1995). Since successful coaches are able to consistently demonstrate the ability to mold a group of individuals into a winning team, it is important to understand what methods coaches employ to develop team confidence. The purpose of this study was to understand how master football coaches develop team confidence. The participants for this interview-based, qualitative study included twenty "master" football coaches (6 professional and 14 collegiate). Criteria for inclusion were as follows: each participant had been a head football coach for at least ten years, and had a consistent record of success. Seventeen of the twenty had achieved success with three or more different teams. The findings reveal that these coaches employ a wealth of psychological strategies in different situations to enhance the development of team confidence. Their selective deployment of these strategies takes place throughout a series of developmental tasks, here described as the "Team Confidence Cycle." This includes seven key tasks: 1. Set the Course, 2. Create a Confidence Environment, 3. Promote Mastery, 4. Get Them to Perform, 5. Assess Performance, 6. Stay the Course and 7. Maintain High Performance. In the interviews the coaches revealed that team confidence was essential to their view of how teams achieve success. The constructs of team confidence and success were considered closely intertwined. Promoting mastery experiences, therefore, was primary among those strategies used by the master coaches to build team confidence. A second key strategy was that they pointed out successful experiences to their team(s). These coaches thus placed the greatest importance on "demonstrating ability" and then ensuring that improvement was noted. These findings are in accordance with Bandura (1997). Implications for coaches, especially of youth sport, are outlined in the final chapter. / 2031-01-01

Limited research data is available outlining the resistance training characteristics of elite football players. The aim of the first study (Chapter 3) was to compare approaches to calculating resistance training volume during 4 weeks of pre-season training in 23 English Premier League footballers. Volume was calculated using four different methods of quantification; Repetition volume (RV), Set Volume (SV), Volume Load (VL) and Maximum Dynamic Strength Volume Load (MDSVL). Overall there was a significant difference between resistance training volumes calculated by the different methods used to monitor resistance training load (P < 0.001). More specifically, significant differences were observed between RV and SV methods (P < 0.001), RV and MDSVL (P = 0.001), SV and VL (P = 0.010), SV and MDSVL (P = 0.033) and VL and MDSVL (P = 0.002). Only RV and VL methods were similar in the information they provided on training load (P = 0.411). While the lack of a gold standard measure of volume makes it is unclear which, if any, method represents the most accurate measure of volume the discrepancies between methodological approaches highlight that these different approaches are not directly transferable as strategies to monitor resistance training. The understanding of the differences between each method may therefore enable appropriate, situation specific, approaches to be designed and implemented for both practical and research purposes. The aim of the second study (Chapter 4) was to analyse the resistance training loads completed by an elite professional football team across a competitive season. Resistance training data was collected from 31 elite football players competing in the English Premier League over a 46 week period in the 2012-2013 season. A total of 1685 individual training observations were collected during the pre-season and in-season competition phases, with a median of 42 training sessions per player (range = 9 – 124). Training load data was separated into 7 blocks of 6 weeks for analysis. These periods included pre-season (6 weeks duration) and in-season (40 weeks duration) phases. Set volume was selected as a measure of total volume. Data was analysed using 3 separate linear mixed modelling analysis using the statistical software package R (Version 3.0.1). Weekly resistance training frequency (mean±SD) ranged from 1±1 to 2±1 sessions per week during the pre and in season phases. Significant differences in session frequency were seen between weeks 1-6 and weeks 7-12 (pre-season) (P ˂ 0.05), weeks 7-12 and weeks 13-18 (P ˂ 0.05), and weeks 7-12 and weeks 37-42 (P ˂ 0.05). Mean weekly training volume ranged from 18±16 to 30±24 sets.wk-1. The total training volume demonstrates a clear minimum during weeks 7-12. Significant differences in total training volume were also observed between weeks 1-6 and weeks 7-12 (pre-season) (P ˂ 0.01), weeks 7-12 and weeks 13-18 (P ˂ 0.05), and weeks 7-12 and weeks 19-24 (P ˂ 0.05). There was no significant difference in training intensity between weeks 1-6 (pre-season) and weeks 7-12. Training intensity during weeks 1-6 however was significantly lower than during weeks 13-18 (P ˂ 0.05), 19-24 (P ˂ 0.01), 25-30 (P ˂ 0.01), 31-36 (P ˂ 0.05), and 37-42 (P ˂ 0.01). Training intensity during weeks 7-12 was also significantly lower than during weeks 13-18 (P ˂ 0.01), 19-24 (P ˂ 0.05), 25-30 (P ˂ 0.05), 31-36 (P ˂ 0.05), and 37-42 (P ˂ 0.001). The findings would suggest that resistance training loading is limited during different periods of the season. This is predominantly as a consequence of low training frequency, potentially due to a high prevalence of competitive fixtures. The aim of the third study (Chapter 5) was to attempt to quantify the impact of resistance training completed by players, through evaluating the change in the lower body power outputs of an elite professional football team across a competitive season. Resistance training data was collected from 22 elite football players competing in the English Premier League over a 38 week period. A total of 246 individual power output observations were collected during the in-season competition phase. Power output of the lower body was assessed using a pneumatic resistance leg press machine with software and digital display (Keiser Sports Health Equipment Inc., Fresno, Ca). Data was analysed by means of linear mixed modelling analysis using the statistical software package R (Version 3.0.1). Power outputs ranged from 2200W to 4078W with a mean value of 3022±374W. Linear mixed effects show a significant effect of week on power output across the season (coefficient= 7.76W, p=0.0132). Specifically, when accounting for within player effects, power output increased 7.76W per week during the season. Individual weekly power coefficients ranged from +39.9W to -18.13W per week, thus indicating that the trend for increased power output across the season is not uniform for all the players. These data may suggest that lower body power performance is maintained or minimally enhanced over the course of a full competitive season in elite football players. Combined with the training load data previously examined in this thesis it can be concluded that whilst one resistance training session per week may be sufficient to avoid in season de-training or minimally improve power performance in elite football players, a frequency of two sessions per week may be necessary to obtain significant performance enhancements. In our fourth study (Chapter 6) we provide two case studies that outline and evaluate a structured approach to increasing resistance training loading with the primary goal of developing strength and power during the competitive season in elite football players. The purpose of our initial case was to examine a resistance training programme to enhance strength and power performance, alongside body composition during a period of rehabilitation from injury. The study intervention commenced following two weeks of recovery following the “Laterjet” surgical procedure. Initial assessments were performed for body composition via dual-energy x-ray absorptiometry (DXA) (QDR Series Discovery A, Hologic Inc., Bedford, MA) and lower body power output via using a pneumatic resistance leg press machine with software and digital display (Keiser Sports Health Equipment Inc., Fresno, Ca). Assessments were repeated 8 weeks post-surgery, i.e. following 6 weeks of resistance training. The six-week intervention consisted of three strength training sessions per week for the initial 3 weeks, followed by 2 sessions per week for the subsequent 3 weeks. Training volume (number of sets) equalled a total of 20 sets total per session. Total increase in body mass over the intervention period equated to 5.4kg, of which 4.2 kg increase in lean mass and a 1.3 kg increase in fat mass. Peak power output increased by 21%. Power to weight ratio also increased by 4.4 %. These data illustrate that it is possible to increase physical performance when rapid short-term increase in resistance training load is completed. The purpose of our second case was to examine a resistance training programme to enhance both strength and power performance parameters during a full competitive season. The player plays as a goalkeeper, regularly playing for his club 1st team. Prior to the onset of this case study this player did not present with any current injuries. This season long intervention consisted of two phases of training. Phase 1 was 16 weeks in duration and represented the beginning to the mid-point of the season. During this phase the goal was to gradually and safely increase resistance training loading. Phase 2 was 20 weeks in duration and represented the mid-point to the end of the season. This phase represented a period of consistent high loading following the initial systematic increase in these variables. / Assessment data was collected at the beginning, mid-point and end of the 2013-14 season. The player was first assessed for body composition via DXA (QDR Series Discovery A, Hologic Inc., Bedford, MA). Secondly, lower body power output was assessed using a pneumatic resistance leg press machine with software and digital display (Keiser Sports Health Equipment Inc., Fresno, Ca). Finally, the player’s upper body strength was assessed via 6 repetition maximum assessments of the dumbell bench press and prone row. The player completed a mean weekly volume of 41±24 sets per week and a mean frequency of 2±1 sessions per week for the initial phase of the study. The player completed a greater mean weekly volume in the later phase of the season compared to the initial training period (65±28 set per week vs. 41±24 sets per week in the initial phase of the season). A greater mean session frequency was also associated with the second training phase (3±1 vs. 2±1 session per week). There was a total decrease in body mass over the initial intervention period of 4kg, of which 2.7kg decrease in fat mass and a further 0.9 kg decrease in lean mass. Over the second phase of the intervention there was a total increase in body mass of 1.2kg, of which 2.4kg increase in lean mass and 1.2kg decrease in fat mass. During the initial phase of training peak power output increased by 25%, whilst power to weight ratio increased by 30%. During the later phase peak power output increased by a further 9% whilst the power to weight ratio increased by a further 10%. Upper body pressing (Dumbell Bench press) and upper body pulling (Dumbell Prone pull) strength was also increased by 14% and 21% respectively during the initial phase and a further 19% and 24% respectively during the later phase of the season.

The work undertaken from the studies in this thesis provides novel information in relation to the physical match demands of the European Super League (ESL) competition, focusing on a newly promoted ESL franchise. Specifically, this is the first work to examine the physical demands of competition for an entire squad of players across an entire competitive season in the ESL, the first to examine the physical demands of match-play over multiple longitudinal seasons, and the first to examine the effects of different between match recovery periods on the running demands for a large sample of ESL teams. Methodological work in this thesis has also highlighted the importance of quantifying and interpreting errors associated with GPS devices to quantify player movements and collisions. Chapter 4 examined the physical match demands for the newly promoted team over the entirety of a competitive season. Significant positional differences were evident, with Outside Backs (OB, 421 ± 89 m) and Pivots (PIV, 306 ± 108 m) performing more sprinting than Middle Unit Forwards (MUF, 185 ± 58 m) and Wide Running Forwards (296 ± 82 m). Conversely, MUF (35 ± 6) and WRF (36 ± 5) performed more collisions than PIV (23 ± 3) and OB (20 ± 3). Practitioners need to be aware of these differences when designing training and conditioning programmes for players. The high speed running (HSR) and number of collisions were greater for the newly promoted team than previously reported for higher ranked ESL teams, but are still lower than those experienced in the southern hemisphere National Rugby League (NRL). Chapter 5 examined the level of agreement between two different models of GPS device in measuring the total distance, and distance covered at high speed (> 5.0 m.s-1) in order that these could be examined in following chapters where two different models of device were used. The two devices showed acceptable levels of agreement in relation to specific analytical goals using positional data from Chapter 4 (total distance CV 0.8%, HSR CV 2.2%) and in relation to the differences between games won and lost at the elite level (mean bias [95% LoA] -0.29 m.min-1 [-1.6 m to 1.01 m.min-1] for total distance per minute, and 0.01 m.min-1 [-0.27 to 0.29 m.min-1] for HSR distance per minute)concluding the two devices could be used interchangeably to measure these parameters. Chapter 6 examined the physical demands of match-play for the newly promoted franchise over a three season period (2012-2014). There was an increase in the physical demands of competition in terms of the total distance coverer per minute (87.0 ± 2.4 m.min-1 – 96.6 ± 2.4 m.min-1), HSR distance covered per minute (6.3 ± 1.3 m.min-1 – 8.1 ± 0.5 m.min-1), and number of collisions per minute (0.43 ± 0.05 no.min-1 – 0.53 ± 0.04 m.min-1). These findings highlight that newly promoted teams need time to develop and adapt to the increasing demands of competition, which is a pertinent issue given the re-introduction of promotion and relegation from 2015. With the current structure, newly promoted teams will not have the chance to plan and develop over the long term, which could leads to teams spending over their means to attract the players required to keep them in the competition rather than focussing on long term player development. Chapter 7 examined the effectiveness of a wearable GPS device to automatically detect collision events during elite Rugby League match-play. The overall error of the device (19%) was associated with not correctly identifying a collision has occurred. Ball carries (97%) were more accurately detected than when compared to tackles (73%). First man tackles (83%) were more accurately detected than second man tackles (72%), and third man tackles (51%). This data suggests the microsensor device has the ability to automatically detect the majority of collision events in Rugby League match-play. However given the collision detection algorithm was originally developed for use in Rugby Union; this may need refinement for use in Rugby League, especially for detecting tackle events. Chapter 8 examined the effect of different between match recovery cycles (short, medium, and long) on the movement demands in subsequent matches on a larger sample of six elite ESL teams. Matches after a short turnaround were associated with greater HSR distance covered per minute of play (13.2 ± 6.9 m.min-1) than when compared to medium (11.6 ± 5.8 m.min-1) and long turnarounds (10.6 ± 5.6 m.min-1). Matches with long turnarounds were associated with increased low speed distance (< 3.8 m.s-1) covered per minute of play (84.8 ± 18.2 m.min-1) than both medium (79.3 ± 19.6 m.min-1) and short turnarounds (80.3 ± 17.7 m.min-1). The total distance covered per minute was only greater on a long turnaround (96.1 ± 16.9 m.min-1) when compared to a medium turnaround(72.9 ± 21.8 m.min-1). These data demonstrate that running performance is affected by the length of the between match recovery cycle, and coaches and conditioning staff working within the ESL should be mindful of these demands when developing recovery and training strategies for their players.