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Examining the Sixth Tool: Analyzing Baseball Specific Character

Examining the Sixth Tool: Analyzing Baseball Specific Character. Dissertation Defense April 16 th , 2013 Seth Haselhuhn , MS, CSCS. Introduction. Major League Baseball (MLB) Scouts evaluate professional baseball prospects on five physical “tools”.

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Examining the Sixth Tool: Analyzing Baseball Specific Character

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  1. Examining the Sixth Tool: Analyzing Baseball Specific Character Dissertation Defense April 16th, 2013 Seth Haselhuhn, MS, CSCS

  2. Introduction • Major League Baseball (MLB) Scouts evaluate professional baseball prospects on five physical “tools”. • Prospects are graded using a 7 point scale. • They also consider the individual characteristics of each prospect and commonly refer to them as the prospect’s “makeup”. • Running • Arm • Hit for power • Hit for average • Defense Tools Grading Scale 20 – CNP 30 – No Prospect 40 – Below Average 50 – Average MLB 60 – Plus 70 – All-Star 80 – Hall of Fame 40 – Below 50 – Average human 60 – Plus

  3. Defining Makeup Although there is very little published regarding the criteria used to evaluate makeup, through conversations with MLB scouts four aspects of makeup become apparent. Risk Taking Motivation Coachability Resilience

  4. Risk Taking “We don’t need choir boys, we need boys who care about the right things.” – Eric Wedge on the role character plays when signing a player. January 29, 2013

  5. Moral Reasoning Hahm-Beller Values Choice Inventory-16 Examines how participants reason in the sport context regarding the moral principles of justice, honesty, and responsibility using a deontic theoretical framework . Targeted towards moral knowing, the first aspect of moral development.

  6. Motivation Motivation is typically defined as a process that influences the initiation, direction, magnitude, perseverance, continuation, and quality of goal directed behavior. • Interaction between an athlete’s respective social-contextual factors and the individual differences between each athlete’s disposition.

  7. “Coachabilty” Conceptions of the Nature of Athletic Ability Questionnaire-2 Examines Dweck’s (2000) entity and incremental self-theories in a sport context. The Stable and Gift subscalesrepresent entity beliefs and the Learning and Improvementsubscales represent incremental beliefs. Targeted towards the situational aspect of athletes’ individual differences regarding motivation.

  8. Motivational Styles Competitive Motivational Styles Questionnaire Examines four motivational styles of athletes including Development Focused, Win-Fixated, Doubt Oriented, and Failure Evader. Targeted towards the dispositional aspect of athletes’ individual differences regarding motivation.

  9. Resilience Mental toughness is an important concept in elite sport performance. With no sport specific instrument to assess mental toughness, researchers have examined similar psychological constructs to assess the concept of individual responses to adversity. Resilienceis a hypothesized correlate of mental toughness.

  10. Resilience Connor-Davidson Resilience Scale Examines individual responses to adversity including: the maintenance of positive adaptation, a capacity or tendency to strive, and an ability to function well. Targeted towards the athletes’ anticipated responses to anxiety and failure.

  11. Purpose of Study The purpose of this quasi-experimental study was to gain a better understanding of baseball specific makeup and begin development of a valid and reliable instrument designed for use by Major League Baseball (MLB) to objectively assess baseball specific personality characteristics (i.e., makeup) of professional baseball prospects.

  12. Hypotheses Sub-Problem One: Ho1: Can a package of instruments be identified to measure baseball makeup? Sub-Problem Two: Ho2: Will modifying items to be baseball specific allow for greater success in identifying baseball makeup? Sub-Problem Three: Ho3: Will the psychological constructs presented in the package of instruments relate to each other in conceptually relevant ways? Sub-Problem Four: Ho4: Can meaningful motivational style profiles for baseball makeup be created? Sub-Problem Five: Ho5: Will there be conceptually relevant differences between motivational style profiles for baseball makeup be evident for this sample?

  13. Methods

  14. Procedures • Collegiate baseball coaches were recruited and directed to a website for access to the package of instruments. • Participants reviewed the directions again and confirmed they were at least 18 years of age. • The original instruments were presented first, starting with the HBVCI-16, followed by the CMSQ, CNAAQ-2, and finally the CD-RISC. • The modified items were presented starting with the HBVCI-16 in the same format as the original • Modified items from the CMSQ and CNAAQ-2, and the original items from the CD-RISC were mixed and presented in a randomized order.

  15. Participants College baseball players comprise the majority of selections in the First Year Player Draft and were targeted for the study. Players currently competing in five divisions of college baseball in six different states participated in the study. A total of 256 logged on to the online survey and the data cleaning process reduced the total sample to 233 participants.

  16. Confirmatory Factor Analysis

  17. Bivariate Correlations

  18. K-Mean Cluster Analysis

  19. MANOVA Wilk’s λ = 0.539, F(12,442) = 13.319, p < .0005; partial ε2 = .27

  20. Canonical Correlation Wilk’s λ values of .38 (p < .0005), .74 (p < .0005), and .91 (p < .0005) respectively. The canonical correlations for the first significant variate was excellent, .70 (49% of the variance), the second significant variate was fair, .43 (18% of the variance), and the third significant variate was questionable, .28 (8% of the variance).

  21. Discussion

  22. Ho1: Can a package of instruments be identified to measure baseball makeup? • The first hypothesis was confirmed. • The package of instruments proposed to measure baseball makeup did produce an acceptable fit using CFA when latent variables were reduced and combined. • Despite the sound fit indexes, observable variables (i.e., items) were removed from the original constructs for the overall analysis. • Therefore further investigation is warranted into sport-specific aspects of each subscale.

  23. Ho2: Will modifying items to be baseball specific allow for greater success in identifying baseball makeup? • The second hypothesis was rejected. • Fit indexes were not as strong as original items. • The modified items produced almost identical correlations between scales. • Subscale means of the modified items were significantly larger than the original items. • In other words, the modified items produced a weaker model and inflated mean thus prompting them to be of little relevance in measuring baseball makeup.

  24. Ho3: Will the psychological constructs presented in the package of instruments relate to each other in conceptually relevant ways? • The third hypothesis was accepted despite the sample population reporting two unexpected, but explainable relationships regarding entity beliefs and moral reasoning. • Support for acceptance is found in both Nicholl’s (1984) and Dweck’s (2000) theories of achievement goals which suggest an orthogonal relationship between ego and task goal orientation and entity and incremental beliefs. • Support for acceptance is also provided by Beller and Stoll (2004) consistent findings that athletes generally report lower moral reasoning scores than their non-athlete peers as well as Campbell-Sills and Stein’s (2007) findings which describe resilience as a situational attribute.

  25. Ho4: Can meaningful motivational style profiles for baseball makeup be created? • The fourth hypothesis was accepted. • Profiles inductively created based on the motivational styles presented in the CMSQ were meaningful both conceptually and pragmatically. • The profiles can be explained academically as well as practically.

  26. Ho5: Will there be conceptually relevant differences between motivational style profiles for baseball makeup be evident for this sample? • The fifth hypothesis was accepted. • The motivational style profiles produced with the CMSQ are the only dispositional variables included in the study. • Based on the profiles developed, results from the HBVCI-16, CNAAQ-2, and CD-RISC produced conceptually sound profile differences in this study.

  27. Recommendations

  28. Internal Recommendations • Collect more performance criteria to better validate cluster results. • Administer package of instruments in person. • Use a more precise moral reasoning instrument to examine the relationship between moral reasoning and motivational profiles.

  29. External Recommendations • An executive summary to participating teams with suggestions for improvement. • An executive summary to the Major League Scouting Bureau’s director for evaluation, consideration, and future research.

  30. Future Research • Continued focus populations expecting to compete on a professional level. • Consideration of cultural differences, specifically Hispanic and Asian cultures. • Development of a user friendly instrument related Rest et al.’s (2000) moral schema theory.

  31. Future Research • Continue to examine the relationship between entity beliefs and positive motivational styles. • Include former college baseball players in the sample for comparison. • Continue to examine the relationship between the DF and DO motivational styles in baseball. • Personal administration of the CMSQ and CNAAQ-2 with follow-up qualitative probes.

  32. Conclusion • Results of the current study are an important addition to the body of knowledge regarding competitive populations in sport. • Specifically, instrumentation designed to assess makeup profiles should target populations with intentions to pursue professional sport. • The results found here provide evidence to support mental skill and moral reasoning education as part of prospect development.

  33. Questions? Photos courtesy of Matt Sanelli

  34. CMSQ Items Removed 1. I always give my best effort. DF Effort Expenditure 5. I choose goals that focus on how I perform. DF Goal Priority 11. After a loss, I want to use practice as a way to improve. DF Response to Failure 15. I work hard in every practice. DF Effort Expenditure 18. I am willing to work a long time to reach my ultimate goal. DF Task Choice 2. Public failures are hard to handle. DO Social 6. I doubt my ability. DO Perceived Ability 10. I feel like a failure when others think I am not skilled. DO S/F Definitions 12. I worry that I won’t perform my best. DO Competitive Outlook 14. I focus too much on the number of mistakes I make. DO Response to Failure 16. I am not as confident as I used to be. DO Perceived Ability 3. Sometimes I try my best, sometimes I don’t try at all. FE Effort Expenditure 8. After a loss, it is difficult to push myself. FE Response to Failure 13. Goals don’t work for me. FE Goal Priority 17. I don’t like to work on my weaknesses. FE Task Choice 20. I avoid setting goals. FE Goal Priority 4. Success to me is winning. WF S/F Definitions 7. My most important goal is to always win. WF Goal Priority 9. Winning is more important than how I perform. WF Goal Priority 19. All my effort is focused on winning. WF Effort Expenditure

  35. CNAAQ-2 Items Removed

  36. Modified CNAAQ-2 Items

  37. Modified CMSQ

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