Autonomy-Supportive Coaching Autonomy-Supporting Coaching

Not unlike the world of business, many researchers and pundits have evaluated and looked at the world of sports as a way to analyze whether and how certain coaching styles are beneficial or non-beneficial in terms of the performance and outcomes of the team in question. Of course, the question is a multi-faceted one and analyzing such a question in a controlled environment can be difficult. Samples sizes and "apples to apples" comparisons can be difficult. Even so, there are many takeaways and points of analysis that can and should be undertaken so as to gauge the efficacy of a team if it is subjected to the supportive-autonomy coaching arc as opposed to other methods.

Autonomy-Supportive Coaching

The subject of this report is an analysis of whether autonomy-supportive coaching is or is not beneficial and effective in boosting performance of the athletes subjected to the method. Not unlike business and other similar situations, it will be assessed whether the leader of the team, typically the coach, can instill and improve performance by using the autonomy-supportive method. Obviously, team dynamics with a spots team are different than a business environment. Even further down the proverbial rabbit hole is pointing out that sports teams dynamics vary based on the game being played due to the number of players on the team or playing field varying, the overall strategy and aggressiveness (or protection) that is required and so forth.

The purpose of this research is really keep away from being too vague and focusing on sports as well as other things and instead drill down on sports teams dynamics in particular and specifically on whether the autonomy-supportive method is worthwhile and effective or not. This research is important because there is surely a way in which some coaches like Nick Saban of Alabama college football fame and Billy Donovan of college basketball fame (among many others) always seem to be in the title race in their respective sports while other teams are perpetual has-beens. Indeed, looking at college and/or pro-sports often comes down to the level of talent and the money coursing through the hands of everyone involved. However, looking at amateur sports and/or high school (or lower) sports is going to be much more enlightening and much easier to analyze in a clean and concise fashion. The general argument to be made by the author of this report, and the guiding force in what is hoped to be proven (or disproven) is whether a team-based environment can produce solid results if certain tactics and habits are engaged in by the team at large as well as the coach. To that end, the author of this report has evaluated players that engage in basketball, hockey, soccer, lacrosse and football. The analysis will be done using performance as the dependent variable and autonomy-supportive coaching as the independent variable. In other words, the same sports environments will be looked at both with and without the dependent variable (the coaching method being assessed) as the difference between the two.

Chapter II - Method

Quantitative/Qualitative Blend

The method of the research study relative to autonomy-supportive coaching can be assessed and summarized using several dimensions. To start, all studies are a blend of quantitative and qualitative studies or they are one or the other. In this case, the study in question as covered in this report is actually a blend. However, quantitative statistics and reports will be the main genesis of the results and the analysis. However, that analysis will be compared and contrasted with the commonly accepted and peer-reviewed research.

Variables

As noted in the introduction, the dependent variable in this research is the performance outcomes both with and without the independent variable, that being the autonomy-supporting coaching style and approach. Coach-led environments will be tried both with and without the autonomy-supportive coaching style. The perceptions, opinions, outcomes and results of the "with" and "without" environments and scenarios will be compared and analyzed using SPSS and other assessment tools both abstract and definite.

Data Collection Methods

The aforementioned quantitative data will be collected using a focus group environment and a general survey. The survey itself, the release and the other forms and details used in this study are summarized and displayed in the appendices of this...

As noted in the variable section, the data will be compiled and summarized using SPSS and data analysis of the same by the writer of this report. The breakdown of the class standing (e.g. freshman, sophomore, etc.), the sport played and so forth will be shown. The results will include the frequency, percent, minimum, maximum, standard deviation, kurtosis and so forth will all be shown and explained.
Chapter III - Results

To put the proper and pressing answer up front, there was no correlation found between the use of the autonomy-supportive coaching style and the results found thereafter. The alpha chronbach reliability of the ASCQ results was 0.67 and the TOPS score was 0.48, both of which indicate fairly low reliability. To show the full results, below is a full breakdown of the class structure and sports type by percentage:

Class Rank

Freshman: 13%

Sophomore: 24%

Junior: 28%

Senior: 35%

As for the sport that was played by the athletes involved, the breakdown of that dimension is as follows:

Sport Played

Basketball: 10%

Tennis: 33%

Hockey: 11%

Soccer: 46%

To drill a bit deeper, a few more results and summary can be explored. First, there was a 66 to 34 split by gender, in favor of men over women. Of course, hockey is normally dominated (if not done exclusively) by women but the other three sports involved are typically available in some form to both men and women. The age of the players involved were roughly college age, ranging from 18 to 23 with a standard deviation of 1.22 and an overall average age of 20.32. In terms of the number of years in the sport, the range was 9 to 18 with the standard deviation being 1.71 while there was an overall average of 13.44. The Kurtosis standard errors scores on both age and sport year was 0.478. The Kurtosis statistic measure was -0.368 and it was 0.159 for the sport year. The overall correlation statistics between coaching style and performance showed a two-tailed sig of 0.746 and a Pearson Correlation of -0.033. As noted before, no correlation was shown between using the autonomy-supportive style and overall performance as compared to the use of no particular method or another method entirely.

Chapter IV - Discussion

While the results of the survey are obviously not consistent with what was expected and predicted by the author of this report, it is safe to say that further research that is based on athletes and situations that are more homogenous and easy to analyze would yield different results and a correlation between autonomy-support styles and future results may still be found. One limitation with this study was the wide dispersion of the sports involved. Perhaps doing this study one sport at a time and analyzing the sports separately would be wise. Indeed, the sports looked at differ greatly in terms of number of people on the playing field, the number of people on the team, the general gender distribution involved (e.g. women rarely play hockey) and so on. Tennis in particular is typically played by a maximum of four people on a court at a given time with there being two teams of two. Other times, it is one on one and there is no team. This stands in contrast to teams like basketball where up to ten people (two teams of five) are on the field at the same time whereas the numbers are different for hockey and soccer depending on the level of play and the gender involved.

Speaking of gender, another limitation is that the survey and focus group pool was 2:1 in favor of the men. This is disappointing given that all but one of the sports involved (hockey) is played widely by both men and men. Even the sports themselves can vary based on gender. For example, professional tennis players that are men play to a best of five sets whereas women typically play best of three. Perhaps the greatest case for the idea that women and men cannot really be lumped together in the same study like this is because men and women, at least on a general level, operate and react quite differently to the same stimuli, as covered and decided on many works and sports are no different as summarized by studies like Habif et al. (2001) and others. Another insight was offered by Conroy and Coatsworth (2007) that dealt with boys and girls (but did not give detail on numbers and such) but also noted that there was no discernible difference in outcome between the genders. That being said, the subjects in question were younger questions and not young adults. Dealing with grown men and women obviously changes things because the genders are obviously different and this becomes protracted and obvious in the adolescent years onward, as noted in Klomsten et al. (2004).

Another factor that is impossible to control…