Impact of loss figures and their predictive factor for future AFL games based on reactance theory (RT) - Lab Report Example

? A study into the impact of loss figures and their predictive factor for future AFL games based on reactance theory (RT) and learned helplessness (LHT) [STUDENT NAME] [UNIVERSITY NAME] Abstract This study used AFL scores from 2007 – 2010 to find out if team performance for a team that loses badly one week, are more likely to lose the next game and if those findings supported reactant theory(RT) or LHT. The hypotheses were firstly that the raw score in the focal game will be worse than the performance in the losing game (LHT) or that performance in the focal game will be better than in the losing game (RT). A second set of hypotheses examined the impact of the size of the loss on the subsequent game and whether the results supported an LHT or RT. The scores found that while RT was slightly supported in the first hypotheses, there was no corresponding correlation in the second hypotheses which results indicated showed limited support for LHT. A study into the impact of loss figures and their predictive factor for future AFL games based on reactance theory (RT) and learned helplessness (LHT) Is it possible to predict the outcome of a future game of Australian Football League (AFL) based on the scores of the game that was played the week before? Reisel and Kopleman (1995) certainly thought it might be possible in some situations when they completed their study that looked at the impact on team performance after a substantial loss. Their study not only considered what happened to a team performance after sustaining a substantial loss; they looked at whether or not the degree of loss suffered (i.e. how big the loss was to the winning team) had an impact on the same team performance by analysing scores in teams where the loss was determined “large” or “very large”. Reisel and Kopleman’s (1995) main focus for their research was the impact of aversive experiences on later team performances due to two possible theories –learned helplessness theory (LHT) and reactance theory (RT). To understand the impact of aversive stimuli on team performances, this paper will first briefly look at the ideas behind both theories, as this is the foundation for the study outlined here. Learned Helplessness Seligman (1975) found that the depression that comes from losing could be considered a state of learned helplessness. He considered that while there were a number of different variables that could contribute to this state, including a loss, he showed that the feelings of defeat and failure could culminate in a belief that the individual had no control over the situation, so that same individual would lose interest in what they were doing. Other symptoms of learned helplessness included a lack of energy, lack of focus and a tendency to blame the loss on their own lack of ability (Seligman, 1975). It is the lack of control over an event that is a key aspect of Seligman’s (1975) theory - or as to put it in his words, the impact of “uncontrollable aversive events”. In his work with Maser (1977) Seligman noted that “learned helplessness is defined as an effect resulting for the uncontrollability of aversive events” (Maser & Seligman, 1977, 33). This would suggest that in a team sport situation, where perhaps the individuals that make up the team perceive the loss of the team as being something they personally had no control over, that this would lead to the learned helplessness that Seligman defined in his 1975 work. Some research work has been done on the perception of ability and actual performance; however they were more to do with any correlation between anxiety/stress on performance rather than prior performance being the motivating factor. Klavora (1974) found that anxiety increased for college basketball players when they moved from regular games during a season through to the playoff competition and this finding was supported by similar work from Gill (1980). In golf, where individual performance is crucial to a positive outcome, Kleine (1990) found there was a negative relationship between anxiety and sports performance. More recently Dweck (2002) supported Seligman’s view about perceptions of ability in that it was not the personal definition of ability that was critical to performance but rather the impact of beliefs held by the individual about their own ability. His work with entity theory showed that those individuals who hold the belief that they have failed are more likely to display the symptoms identified by Seligman’s (1975) idea of learned helplessness. Reactance Theory Brehm (1966) defined psychological reactance as “the motivation of an individual to reinstate lost or threatened freedoms” (Dowd, Pepper & Seibel, 2001, 239). It was his theory that if an individual experienced a loss or a threatened loss of a specific “freedom” then rather than try and achieve new freedoms, instead he would put a lot of effort into regaining the freedoms that had been lost or threatened. Although Brehm’s (1966) did not identify what those freedoms were, preferring instead to say simply that they freedoms were best understood in the context of any given situation (Dowd et al, 2001, 239) more recent researchers have considered a wide range of different situations that could be considered freedoms, including achievement in sports. Brehm and Brehm (1981) looked at the idea that the individual’s perceptions of freedom were impacted by life experience and socialization. Dowd et al (2001) found in their earlier studies that psychological reactance was found in a certain type of individual; namely male and a Type A personality. These aspects would be important when determining a sports team reaction to a large loss against another team. Dowd and Wallbrown (1993) found that high reactant individuals are likely to be more defensive, aggressive, dominant and autonomous. However their studies also showed that a lower need for affiliation was also evident in this type of person – which does not relate well to a team situation where perhaps the concepts of camaraderie and reliance on others to do well, is a more likely situation. Still later studies by Dowd, Wallbrown, Sanders and Yesenosky (1994) found that reactant individuals were not overly worried about creating a good impression on others; they were less tolerant of the beliefs of others; they were more likely to resist rules and regulations; they were not too worried about meeting obligations and they were more likely to express strong emotions. One last point relevant to this study about reactance is the positive correlation between reactance and autonomy (Dowd 1993; Dowd & Seibel, 1990). This aspect brings us back the perception of the individual in relation to how they might respond to a big loss in a sports game. If the individuals in the losing team had a strong confidence in themselves, then based on this literature it would be likely that the reactant theory was more likely to influence the performance of the team in a future game. Purpose of Research What we have here is two clear different responses to a situation. Under LHT a loss would be considered something that was outside of the individual’s or teams control. For an individual this might lead him to think he is a bad player; that the loss was his fault because he was not good enough; and therefore the loss was out of his control. This line of thinking in a number of individuals in the team would result in team members giving up, reducing the amount of effort they would put into a future game and a negative performance overall. Possible situations that might cause that line of thinking could include ideas such as “the other team was just too good”, “we are not very good players” or thoughts along those lines among individuals in the team, and the general team mood after the game has finished. Under reactance theory a loss in a sports game would be considered by the individual to be something that he could overcome through greater effort and improved performance – in this sense the aversive experience (losing the game) would be seen as a motivator for increased effort next time out. If the team culture supported similar feelings – that “you just need to redouble your efforts next time;” that the ability of the players was something that could be improved and the players were the type of individuals that saw loss as a challenge rather than as an indictment, then it would suggest that the impact on the outcome of a future game was likely to be more positive. Research Questions As already mentioned the aversive stimuli this paper will study is the impact of a large loss in one game on subsequent team performance in their next game. The study will be based on analysis of the game scores for AFL games in the 2007 to 2010 seasons. This is a similar type of research model as the study conducted by Reisel and Kopleman’s (1995). The plan is to consider two research questions: 1. What is the impact of a large loss on subsequent performance of an AFL team? 2. Does the impact of a large loss on subsequent performance of an AFL team depend on the size of the loss – for example “large” vs. “very large”? In the first question the hypothesis will be based on the idea that under reactance theory the performance of the team will improve; while under LHT the performance will actually decline in the subsequent game. The second hypothesis will look at the correlation between the size of the loss and the degree of changed performance from one game to the next. If reactance theory is indicated then the results should show that the larger the loss was in the first game, the greater the improvement will be in the subsequent game. If LHT is indicated then it is expected that the greater the loss is in one game, the greater the decrease in performance will be evident in the subsequent game. Overall the focus of this study will be on which of the two theories, reactant theory and LHT, is most predictive in terms of the observed performance of AFL sports teams. The aversive stimuli or event is the large loss in one game and the standard of performance in the same team, in a subsequent game. Hypotheses There are two hypotheses that will be tested for each research question above. For the research question one, the hypotheses are (H1A, H1B): That performance (raw score only) in the focal game will be worse than the performance in the losing game (LHT theory). Performance in the focal game will be better than the performance in the losing game (RT) For the second research question the hypotheses are (H2A, H2B): When the loss is larger in the losing game, improvement in performance in the focal game will be smallest (LHT). When the loss is larger in the losing game, improvement in performance in the focal game will be greatest (RT). Method Procedure The data collection for this study came from the scores of AFL games between 2007 and 2010. According to the AFL website (http://www.afl.com.au) each season between and including 2007 and 2010 hosted 16 teams to play in a total of 22 rounds before the three finals weeks and the grand final for each year. That equates to 8 games per round which results in 176 games for each of the four seasons. This gives us 704 games in total not including the games for the finals weeks, and the grand final. To ensure that no additional variables might have been responsible for team performance the following matches were taken out of the data collection: The first and last games in the 22 rounds per season The games relating to the three finals weeks and the grand final for each of the four seasons The games that resulted in a draw. Over four seasons this was a total of 9 games. The total number of games used in this study was 631 games. This resulted from 176 games each season; minus the 16 games played in rounds one and twenty two; minus the 9 games over the four seasons that resulted in a draw. Measures One of the challenges of this study was identifying what could be considered a “very large loss” and what could be considered just a “large loss”. In sports vernacular those terms are used quite often and yet no specific loss difference is usually meant or implied. In a game like Australian Football a team that was scoring high on the points table might be considered to have suffered a “huge” loss if they were to lose by 20 points to a bottom ranked team on any given week. To determine the point’s difference for both loss and large loss it was decided to use an average of losses by each team and then identify the differences in those games where the loss was statistically high based on a percentage. For this study it meant that a very large loss would equal a difference in scores of 60 or more points. Over the four seasons analysed this happened just 16% of the time and was considered quite rare. For the large loss figures all games with score differentials of between 42 to 59 points were considered. This happened 17% of the time, which was not often. So for the purpose of this study a losing game was a game where the loss was ? 42 points. In the data for this study it was noted that the substantial loss occurred 33% of the time and there was a similar frequency for large and very large loss. In total there were 211 games out of the original 631 games over four seasons where the substantial losses (? 42 points) occurred. Performance Measures With regards to performance not all of the measures used in Reisel and Kopleman (1995) were used. This study used a raw score which was the performance in a focal game – one that occurs after a game where a substantial loss was experienced. A net score was defined as the combination of the (-Game preceding game loss) minus (-the focal game loss) = (- net score) So for example if the preceding game was lost by 47 points; and the focal game was lost by 50 points then the net score would be -3. In this example the team performance was 3 points worse after a large loss compared to the performance prior to a large loss. Results For hypotheses 1A (performance would be worse in the focal game than in the losing game, LHT) the paired samples test showed that for n=211, the mean for the losing game was higher (M= -63.60; S.D. = 19.40) than in the focal game (M=-9.05; S.D. 40.75). This would suggest that LHT was not a factor in the results found here. For hypotheses 1B (performance in the focal game will be better than the performance in the losing game, RT) the same results above showed that there was a significance in the paired samples correlation test (N= 211). The correlation was not overly high (0.136) but the significance was evident (p=0.48). This would suggest that RT was a factor in the results. For hypotheses 2A (when the loss is larger in the losing game, improvement in the focal game will be smallest, LHT) the variables tested were large v. very large loss. For the focal group (large – where raw score was 42-59) n=108, M= -2.16, S.D. = 40.109; by comparison the results for the focal group (very large where raw score was >60), n=103, showed a greater mean (M=-16.27), but a similar standard deviation (S.D. = 40.355). This was not considered significant when equal variances were assumed (p = .834). The two-tailed t-test for equality of means t=2.547, df = 209 did show a significance (p=.012) for the focal variable. For this variable there was some support found for LHT. For hypotheses 2B (when the loss is larger in the losing game, improvement in performance in the focal game will be greatest, RT) the higher mean (m=12.42) was found for the score group 42-59 (large) rather than the >60 group. In the independent samples test for the net scores f = .04; p= .952 showing there was not a significant correlation there. In the t-test for equality of means t=2.38, df=209, p=0.018. RT was not supported for RT. To sum up the results in the first hypothesis the team performance was substantially better in the focal game compared to the losing game (H1 A null, H1b true). For the second question where both raw scores and net scores were tested, the results showed that in the case of a greater initial loss this resulted in a slightly higher loss in the focal game (H2A true, H2B null). Discussion The results in this study were not overwhelmingly conclusive although they did show a consistence with reactance theory for hypothesis 1A. In hypotheses 2A and 2B, where the question was focused on whether the size of the initial loss was important to the focal game score, this was not supported for reactance theory, but provided some limited support for LHT. The teams that lost by more than 60 points in a game, did lose more (net score) than the teams who lost by 42-59 points. But all of the teams performed better after a substantial loss which supported reactance theory. This study showed similar problems to others done on sports performance and the impact of reactance and LHT on performance. Reisel and Kopleman (1995) considered the difficulty of the teams in the focal game, which was not covered here and there was also no provision for the impact other variables might have on overall team performance. Another significant difference between this study and the one conducted by Reisel and Kopleman (1995) is that the data for this study constitutes 33% of all scores collected; Reisel and Kopleman (1995) only used 17% of the available data for their work. It is possible that the size of the population might have an impact on the overall findings. Another important variable not included in this study but was a feature of Reisel and Kopleman’s (1995) study was that they adjusted their scores according the point spreads of each matches. They used this variable to even out the various playing levels of the teams. This study did not include that data. One of the reasons why it might be difficult for researchers to come to a solid conclusion about this is because teams are a combination of individuals. It is possible that one of the reasons the findings in this study were not that conclusive were because some members of a team might be typified as being more reactant while others might be more inclined to LHT in the face of adversity. As it is reasonable to assume that each team may have a different percentage of RT and LHT in their make-up that may impact the overall team environment. This study did not consider any variables that might have impacted team performance between the first and focal game. For example did the coaches of any of the teams try and motivate their teams after a larger or very large loss – or did their behaviour reinforce the LHT feelings that might be evident in the team. Consideration of coach input, the impact of supportive or non-supportive partners outside of the team environment were not factored into this research. Thomas (1996) who conducted his study on basketball players moving into the playoffs found that his study did not support the LHT theory as he had original hypothesized it would. He found that players of all ability levels showed a decrease in productivity during the playoffs and that individually they were no more immune to LHT than any players of a higher or lower ability level. Thomas (1996) felt that this might have been because his study was based on personal scoring statistics which would be lower during the playoffs due to the higher level of competition. In Dowd and Wallbrown (1993) they found that reactant theory was an individual state and that the profile of a reactant individual was someone who was “aloof from others, mistrustful of them, and lacking in strong affiliate ties” even to the point of being considered “loners” (p.536). This could be one reason why although the results of this study did show some support for reactant theory, it was not an overwhelmingly significant finding. One of the important aspects of any future research in this topic is the standardization and increase in the number of variables being tested. Team behaviour and performance are all impacted by the belief systems and perceptions of self and ability for individuals. The team too, as a unit has it own belief structure and culture and these aspects could also have a significant impact on whether or not the team would respond positively to a loss, or more in line with LHT. In conclusion this study did find some support for the emergence of reactant theory in the differences between the first and focal matches. The hypothesis relating to the impact the size of the difference of the loss was not supported by reactant theory but there was some evidence that LHT might have been a factor. Because of the high number of variables that do impact both individual and team importance future research might want to come up with a methodology that includes the higher number of variables, and a way of reducing the number of limitations found in this and Reisel and Kopleman’s (1995) study. References Brehm, J. W. (1966). A theory of psychological reactance. New York: Academic Press. Brehm, J. W., & Brehm, S. S. (1981). Psychological reactance. New York: Wiley. Dowd, E. T. (1993). Motivational and personality correlates of psychological reactance and implications for cognitive therapy. Psicologia Conductual, 1, 131-140. Dowd, E. T., & Seibel, C. (1990). A cognitive theory of resistance and reactance: Implications for treatment. Journal of Mental Health Counseling, 12, 458-469. Dowd, E. T., & Wallbrown, F. (1993). Motivational components of psychological reactance. Journal of Counseling & Development, 71, 533-538. Dowd, E. T., Wallbrown, F., Sanders, D., & Yesenosky, J. M. (1994). Psychological reactance and its relationship to normal personality variables. Cognitive Therapy and Research, 18, 601-612. Dowd, T., Pepper, H.F., Seibel, C. (2001). Developmental correlates of psychological reactance. Journal of Cognitive Psychotherapy, 15(3), 239+ Dweck, C.S. (2002). The development of ability conceptions. In A. Wigfield & J.S. Eccles (Eds.) Development of Achievement Motivation (pp.57-88) New York: Academic Press Gill, D. L. (1980). Comparison of three measures of pre-competition arousal. Perceptual and Motor Skills, 51, 765-766. Klavora, P. (1974). State anxiety and athletic competition. Unpublished doctoral dissertation, The University of Alberta-Edmonton. Kleine, D. (1990). Anxiety and sport performance: A meta-analysis. Anxiety Research, 2, 113-131. Maser, J. D., & Seligman, M. E. P. (1977). Psychopathology: Experimental models. San Francisco: Freeman Reisel, W. D. & Kopleman, R. E. (1995). The Effects of Failure on Subsequent Group Performance in a Professional Sports Setting. The Journal of Psychology, 129, 103-113. Seligman, M. E. P. (1975). Helplessness: On depression development and death. San Francisco: Freeman. Thomas, G. (1996). Learned helplessness and basketball playoff performance. Journal of Sports Behavior, 19(4), 347+ Appendix 1: Results Read More