{"id":258,"date":"2008-03-14T14:03:36","date_gmt":"2008-03-14T14:03:36","guid":{"rendered":""},"modified":"2013-11-26T15:52:43","modified_gmt":"2013-11-26T15:52:43","slug":"use-of-the-athletic-coping-skills-inventory-for-prediction-of-performance-in-collegiate-baseball","status":"publish","type":"post","link":"https:\/\/thesportjournal.org\/article\/use-of-the-athletic-coping-skills-inventory-for-prediction-of-performance-in-collegiate-baseball\/","title":{"rendered":"Use of the Athletic Coping Skills Inventory for Prediction of Performance in Collegiate Baseball"},"content":{"rendered":"
Submitted by: Sandy Kimbrough, Louisa DeBolt & Richard S. Balkin<\/div>\n

Abstract<\/strong><\/p>\n

The Athletic Coping Skill Inventory (ACSI-28) was completed by twenty-six
\ncollegiate baseball players. Performance statistics were collected, including
\nbatting average (BA), number of errors committed (ERR), and earned run
\naverage (ERA) for pitchers. Regression analysis was carried out using
\nthe seven areas of the ACSI-28 (peaking under pressure, freedom from worry,
\ncoping with adversity, concentration, goal setting and mental preparation,
\nconfidence and achievement motivation, and \u2018coachability\u2019)
\nas the independent variables, and the current season\u2019s performance
\nstatistics as the dependent variables. Correlation coefficients revealed
\nsignificance between concentration, confidence, and ERA, while there were
\nno significant relationships with BA or ERR and any of the psychological
\nvariables. Many of the psychological variables were highly related. While
\nsequential linear regression did not reveal statistically significant
\nrelationships between the performance statistics and the psychological
\nvariables, large effect sizes indicated a strong degree of practical significance.
\nSpecifically, peaking under pressure and \u2018coachability\u2019 appeared
\nto be strong predictor variables for ERA, concentration for ERR, and \u2018coachability\u2019
\nfor BA.<\/p>\n

<\/p>\n

Introduction<\/strong><\/p>\n

Athletes and theorists in human performance agree on the influence of
\npsychological factors in the performance of motor skills, particularly
\nat a high level of competition. As a result, an abundance of research
\nhas been dedicated to finding out not only how to prepare athletes mentally
\nfor high-pressure situations, but also what psychological factors are
\nspecifically determinants of performance. The link between research and
\napplication is of great importance because the business of sports is at
\nan all-time peak and athletes from early childhood to advanced age are
\nseeking ways to improve their game not only physically but mentally.<\/p>\n

The use of self-reporting instruments that indicate specific psychological
\nskills is widespread, especially in collegiate and professional athletics.
\nBecause of the comparable levels of physical abilities among top-tier
\nathletes, coaches seek to understand which psychological factors separate
\nthe elite from the non-elite. In sports where \u201cchoking\u201d may
\ncost a player or team a championship ring or millions of dollars, it is
\nunderstandable that non-invasive, simple indicators of psychological skill
\nmeasures have become popular.<\/p>\n

The baseball skills of pitching, hitting, and fielding are arguably as
\nmental as they are physical. Pressure can affect a pitcher at any point
\nin the game; managers and pitching coaches make it their business to \u201cknow\u201d
\nwhich pitchers will crumble under pressure and which will rise to the
\noccasion. Certainly, if a method for predicting correctly the mental toughness
\n(coping, if you will) of an athlete was shown to be valid and reliable,
\nit would be of great benefit to coaches, managers, and athletes alike.<\/p>\n

The Athletic Coping Skills Inventory (ACSI-28), created in 1988, contains
\nseven sport specific subscales: coping with adversity (COPE), peaking
\nunder pressure (PEAK), goal setting\/mental preparation (GOAL), concentration
\n(CONC), freedom from worry (FREE), confidence and achievement motivation
\n(CONF), and \u2018coachability\u2019 (COACH) (Smith, Schutz, Smoll,
\n& Ptacek, 1995). Smith and Christensen (1995) defined the subscales
\nas follows as they apply to the sport of baseball:<\/p>\n

Peaking under Pressure: is challenged rather than threatened by pressure
\nsituations and performs well under pressure; a clutch performer<\/p>\n

Freedom from Worry: does not put pressure on self by worrying about
\nperforming poorly or making mistakes; does not worry about what others
\nwill think if he\/she performs poorly<\/p>\n

Coping with Adversity: remains positive and enthusiastic even when
\nthings are going badly; remains calm and controlled; can quickly bounce
\nback from mistakes and setbacks<\/p>\n

Concentration: not easily distracted; able to focus on the task at
\nhand in both practice and game situations, even when adverse or unexpected
\nsituations occur<\/p>\n

Goal Setting and Mental Preparation: sets and works toward specific
\nperformance goals; plans and mentally prepares self for games and clearly
\nhas a \u201cgame plan\u201d for pitching, hitting, playing hitters,
\nbase running, and so on<\/p>\n

Confidence and Achievement Motivation: is confident and positively
\nmotivated; consistently gives 100% during practice and games and works
\nhard to improve skills<\/p>\n

\u2018Coachability\u2019: open to and learns from instruction; accepts
\nconstructive criticism without taking it personally or becoming upset
\n(p. 402).<\/p><\/blockquote>\n

Smith and Christensen (1995) studied the usefulness of the ACSI as a
\nperformance prediction tool in an elite athlete population, namely professional
\nbaseball players. The participants were 104 minor league baseball players
\n(forty-seven pitchers and fifty-seven position players) of the Houston
\nAstros organization. Participants completed the ACSI during spring training;
\nbatting averages (BA) for the position players and earned run averages
\n(ERA) for the pitchers were used as performance indicators. For position
\nplayers, only CONF was a significant predictor of BA, while ERA for pitchers
\ncorrelated significantly with CONF and PEAK scores. High CONF and PEAK
\nscores were related to lower ERA\u2019s. Interestingly, ACSI results
\nwere predictive of survival in professional baseball two and three years
\nafter the testing was conducted and ACSI predicted ERA better than coaches\u2019
\nratings of physical skill.<\/p>\n

Guarnieri, Bourgeois, and LeUnes (1998) used the ACSI with aspiring baseball
\numpires at three professional umpire training schools in Florida. They
\nfound that the more experienced umpires used athletic coping skills more
\neffectively than did those in training. Little research has been done
\nwith the ACSI recently, other than the development of a Greek version
\nin 1998 (Goudas, Theodorakis, and Karamousalidis), and its usefulness
\nas a predictive tool for success in sport may remain to be seen.<\/p>\n

The purpose of the current study was to examine the usefulness of the
\nACSI in predicting BA, ERA, and errors (ERR) for collegiate baseball players.
\nThe seven skills identified by the ACSI at surface level appear to be
\nrelated not only to each other, but also to success in discrete motor
\nskills in baseball that are always performed in the context of pressure:
\nbatting, pitching, and fielding.<\/p>\n

Method<\/strong><\/p>\n

Participants<\/em><\/p>\n

Participants were twenty-six collegiate baseball players from the same
\nteam that were active players during the 2005 season (twelve pitchers,
\nthirteen position players, and one pitcher\/position player). The players
\nsigned a consent form that assured them that their responses would only
\nbe used for research purposes and would not be seen by any member of the
\norganization or any other individual other than the investigators. None
\nof the athletes had played baseball professionally.<\/p>\n

Procedure<\/em><\/p>\n

The ACSI (see Appendix) was distributed to the players at a regular meeting
\nof the team and instructions were read by the investigator. After the
\nparticipants signed and returned an informed consent form, they completed
\nthe ACSI-28. Participants were instructed to consider each item and answer
\nwithout consulting any other individuals. The procedure took about ten
\nminutes, and all participants completed the instrument as instructed.
\nEach participant also indicated on the instrument his\/her position, year
\nof eligibility, and scholarship status (full, partial, or none). Statistics
\nfrom the 2005 baseball season were collected; batting average (BA), number
\nof errors committed (ERR), and earned run average (ERA) for pitchers were
\ncomputed.<\/p>\n

Statistical Analysis<\/em><\/p>\n

The statistical analyses were carried out in three stages using SPSS
\nversion 13.0 for windows (SPSS, 2004). First, data screening and descriptive
\nstatistics were completed to examine participant characteristics. Regression
\nanalysis was carried out using the seven areas of the ACSI (COPE, PEAK,
\nGOAL, CONC, FREE, CONF, and COACH), as the independent variables, and
\nthe current season\u2019s earned run average (ERA05), and batting average
\n(BA05) as the dependent variables. The primary outcome measures were analyzed
\nusing three separate regression analyses. Differences (p<\/em> values)
\nof less than .05 were considered statistically significant.<\/p>\n

Results<\/strong><\/p>\n

After data collection, all variables were entered for analysis and screened
\nto determine if statistical assumptions were met. This screening included
\nexaminations for distribution linearity and outliers. All statistical
\nassumptions were met for the variables.<\/p>\n

In the current study, baseball players were broken down by position, scholarship,
\nand class level. Of this group, 54% were pitchers (n = 14), 23% were infielders
\n(n = 6), and 23% were outfielders (n = 6). Only one athlete did not receive
\na scholarship; 85% percent of the athletes were on partial scholarships
\n(n = 22), and 11% were on full scholarships (n=3). Lastly, 27% were freshman
\n(n = 7), 19% were sophomores (n = 5), 19% were juniors (n = 5), and 35%
\nwere seniors (n = 9). When examining the relationships between variables,
\nPearson Product moment correlation coefficients revealed significance
\nbetween CONC, CONF, and ERA05, while there were no significant relationships
\nwith BA05, ERR05, and any of the independent variables (Table 1). For
\nthe psychological skills variables, COPE was significantly related to
\nPEAK, GOAL, and CONC. PEAK was significantly related to CONC and FREE.
\nLastly, CONF, COACH, GOAL, and CONC were significantly related. These
\ncorrelations were moderately correlated, and ranged from r = 0.444 – 0.541
\n(see Table 1).<\/p>\n

Table 1. Descriptive statistics and correlation coefficients between
\nACSI variables and performance statistics.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Variable<\/td>\nM<\/td>\nSD<\/td>\nAVG04<\/td>\nAVE05<\/td>\nERA05<\/td>\nERR05<\/td>\nCOPE<\/td>\nPEAK<\/td>\nGOAL<\/td>\nCONC<\/td>\nFREE<\/td>\nCONF<\/td>\nCOACH<\/td>\n<\/tr>\n
BA05<\/td>\n0.30<\/td>\n0.13<\/td>\n0.50<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
ERA05<\/td>\n6.98<\/td>\n2.70<\/td>\n0.32<\/td>\nNA<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
ERR05<\/td>\n4.00<\/td>\n3.99<\/td>\nNA<\/td>\n0.34<\/td>\nNA<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
COPE<\/td>\n2.04<\/td>\n0.48<\/td>\n-0.34<\/td>\n-0.13<\/td>\n-0.16<\/td>\n0.03<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
PEAK<\/td>\n2.41<\/td>\n0.57<\/td>\n-0.34<\/td>\n-0.19<\/td>\n-0.23<\/td>\n-0.03<\/td>\n.521*<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
GOAL<\/td>\n1.74<\/td>\n0.71<\/td>\n-0.19<\/td>\n-0.30<\/td>\n0.11<\/td>\n-0.17<\/td>\n.541*<\/td>\n0.32<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
CONC<\/td>\n2.41<\/td>\n0.41<\/td>\n-0.19<\/td>\n-0.17<\/td>\n-0.08<\/td>\n-0.41<\/td>\n.444*<\/td>\n.606*<\/td>\n.485*<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
FREE<\/td>\n1.74<\/td>\n0.73<\/td>\n0.08<\/td>\n-0.01<\/td>\n-0.12<\/td>\n-0.10<\/td>\n0.22<\/td>\n.447*<\/td>\n0.02<\/td>\n0.33<\/td>\n—-<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
CONF<\/td>\n2.63<\/td>\n0.39<\/td>\n-0.24<\/td>\n-0.02<\/td>\n0.22<\/td>\n0.14<\/td>\n-0.07<\/td>\n0.31<\/td>\n0.01<\/td>\n0.13<\/td>\n.408*<\/td>\n—-<\/td>\n<\/td>\n<\/tr>\n
COACH<\/td>\n2.52<\/td>\n0.48<\/td>\n0.25<\/td>\n0.31<\/td>\n0.37<\/td>\n0.23<\/td>\n-0.13<\/td>\n0.17<\/td>\n-0.10<\/td>\n0.05<\/td>\n0.31<\/td>\n.408*<\/td>\n—-<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

*p<.05<\/p>\n

Sequential linear regression was used to determine significant psychological
\npredictors of ERA05 , ERR05, and BA05. There was not a statistically significant
\nrelationship among the predictors and ERA05, F<\/em>(7,6) = .507, p<\/em>
\n= .802. A large effect size was evident, R2<\/sup><\/em> = .37, indicative
\nof a strong degree of practical significance. Peaking and coaching appear
\nto be stronger predictor variables, each uniquely accounting for 5% of
\nthe variance in the model (see Table 2).<\/p>\n

Table 2
\nResults of Multiple Regression Analysis<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Variable<\/td>\nB<\/td>\nSE B<\/td>\n\u00df<\/td>\nsr2<\/td>\n<\/tr>\n
Regression for ERA<\/td>\n<\/tr>\n
coping with adversity<\/td>\n0.53<\/td>\n3.06<\/td>\n0.13<\/td>\n0.00<\/td>\n<\/tr>\n
peaking under pressure<\/td>\n-2.24<\/td>\n3.04<\/td>\n-0.54<\/td>\n0.05<\/td>\n<\/tr>\n
goal setting\/motivation<\/td>\n0.39<\/td>\n2.28<\/td>\n0.10<\/td>\n0.00<\/td>\n<\/tr>\n
concentration<\/td>\n-0.26<\/td>\n2.50<\/td>\n-0.06<\/td>\n0.00<\/td>\n<\/tr>\n
freedom from worry<\/td>\n-0.41<\/td>\n1.80<\/td>\n-0.12<\/td>\n0.01<\/td>\n<\/tr>\n
confidence<\/td>\n1.86<\/td>\n3.67<\/td>\n0.45<\/td>\n0.03<\/td>\n<\/tr>\n
‘coachability’<\/td>\n2.02<\/td>\n2.84<\/td>\n0.47<\/td>\n0.05<\/td>\n<\/tr>\n
Regression for Errors<\/td>\n<\/tr>\n
coping with adversity<\/td>\n4.77<\/td>\n4.22<\/td>\n0.74<\/td>\n0.07<\/td>\n<\/tr>\n
peaking under pressure<\/td>\n3.25<\/td>\n3.08<\/td>\n0.67<\/td>\n0.06<\/td>\n<\/tr>\n
goal setting\/motivation<\/td>\n-0.98<\/td>\n2.44<\/td>\n-0.18<\/td>\n0.01<\/td>\n<\/tr>\n
concentration<\/td>\n-11.45<\/td>\n3.95<\/td>\n-1.87<\/td>\n0.49<\/td>\n<\/tr>\n
freedom from worry<\/td>\n-0.25<\/td>\n2.58<\/td>\n-0.05<\/td>\n0.00<\/td>\n<\/tr>\n
confidence<\/td>\n0.82<\/td>\n2.76<\/td>\n0.16<\/td>\n0.01<\/td>\n<\/tr>\n
‘coachability’<\/td>\n3.77<\/td>\n2.58<\/td>\n0.72<\/td>\n0.12<\/td>\n<\/tr>\n
Regression for Batting Average<\/td>\n<\/tr>\n
coping with adversity<\/td>\n0.19<\/td>\n0.18<\/td>\n0.84<\/td>\n0.10<\/td>\n<\/tr>\n
peaking under pressure<\/td>\n-0.09<\/td>\n0.13<\/td>\n-0.51<\/td>\n0.04<\/td>\n<\/tr>\n
goal setting\/motivation<\/td>\n-0.08<\/td>\n0.10<\/td>\n-0.39<\/td>\n0.05<\/td>\n<\/tr>\n
concentration<\/td>\n-0.01<\/td>\n0.17<\/td>\n-0.03<\/td>\n0.00<\/td>\n<\/tr>\n
freedom from worry<\/td>\n0.03<\/td>\n0.11<\/td>\n0.16<\/td>\n0.01<\/td>\n<\/tr>\n
confidence<\/td>\n-0.09<\/td>\n0.12<\/td>\n-0.48<\/td>\n0.05<\/td>\n<\/tr>\n
‘coachability’<\/td>\n0.14<\/td>\n0.11<\/td>\n0.79<\/td>\n0.15<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

There was not a statistically significant relationship among the predictors
\nand ERR05, F<\/em>(7,7) = 1.46, p<\/em> = .315. A large effect size
\nwas evident, R2<\/sup><\/em>= .59, indicative of a strong degree of practical significance.
\nCONC was the strongest predictor, uniquely accounting for 49% of the variance
\nto the model. COACH was also a strong predictor, uniquely accounting for
\n12% of the variance to the model. COPE uniquely accounted for 7% of the
\nvariance to the model. PEAK uniquely accounted for 6% of the variance
\nto the model.<\/p>\n

There was not a statistically significant relationship among the predictors
\nand BA05, F<\/em>(7,7) = .60, p<\/em> = .745. A large effect size
\nwas evident, R2<\/sup><\/em> = .37, indicative of a strong degree of practical
\nsignificance. COACH was the strongest predictor, uniquely accounting for
\napproximately 15% of the variance to the model. COPE uniquely accounted
\nfor 9% of the variance to the model. GOAL and CONF each uniquely accounted
\nfor 5% of the variance to the model.<\/p>\n

Discussion<\/strong><\/p>\n

The results of this exploratory study indicate that the usefulness of
\nthe ACSI in predicting performance outcomes in collegiate baseball may
\nbe of benefit. Due to the small sample size of this study, coupled with
\nthe large number of predictor variables, no statistical significance was
\nfound in any of the relationships. However, the large effect sizes for
\nall three criterion variables were indicative of a strong degree of practical
\nsignificance. Specifically, concentration appears to be strongly related
\nto errors, and \u2018coachability\u2019 to batting average. To even
\na casual observer of baseball, this observation may seem to be simply
\ncommon sense. The usefulness of the ACSI-28 may be designed for managers
\nof relatively young teams where batting order, starting positions, and
\npitching strategies have not yet been determined. If a coach knows (with
\nsome certainty) which players are can be coached and which can maintain
\nhigh levels of concentration, the coach\u2019s decisions can be based
\nmore on fact than feeling. Please note that the use of the ACSI does not
\nguarantee success of the athletes who complete it or coaches who make
\ndecisions based on it. However, I strongly suggest that managers take
\nadvantage of these findings and add the ACSI-28 to their arsenal for strategic
\ndecision-making.<\/p>\n

Future research in this area should focus on obtaining larger sample
\nsizes. An increase in statistical power would likely identify statistically
\nsignificant relationships, given the meaningfulness of the predictor variables
\nin this study.<\/p>\n

References<\/strong><\/p>\n

Goudas, M., Theodorakis, Y., and Karamousalidis, G. (1998). Psychological
\nskills in
\nbasketball: Preliminary study for development of a Greek form of the Athletic
\nCoping Skills Inventory-28. Perceptual and Motor Skills<\/em>, 86(1),
\n59-65.<\/p>\n

Guarnieri, A., Bourgeois, T., and LeUnes, A. (1998). A psychometric
\ncomparison of
\ninexperienced and minor league umpires<\/em>. Paper presented at the meeting
\nof the Association for the Advancement of Applied Sport Psychology, Hyannis,
\nMA.<\/p>\n

Smith, R. E., and Christensen, D. S. (1995). Psychological skills as
\npredictors of
\nperformance and survival in professional baseball. Journal of Sport
\nand Exercise Psychology<\/em>, 17, 399-415.<\/p>\n

Smith, R. E., Schutz, R. W., Smoll, F. L, and Ptacek, J. T. (1995). Development
\nand
\nvalidation of a multidimensional measure of sport-specific psychological
\nskills: the Athletic Coping Skills Inventory-28. Journal of Sport
\nand Exercise Psychology<\/em>, 17, 379-398.<\/p>\n

SPSS Version 13.0 [Computer Software]. (2004). Chicago, IL: SPSS.<\/p>\n

Appendix<\/strong><\/p>\n

ACSI SURVEY
\nNAME:
\nPOSITION: OF INF P C
\nYR: F SO JR SR
\nSCHOLARSHIP: NONE PARTIAL FULL<\/p>\n

0 = ALMOST NEVER, 1 = SOMETIMES, 2 = OFTEN, 3 = ALMOST ALWAYS<\/p>\n

    \n
  1. On a daily or weekly basis, I set very specific goals for myself that
    \nguide what I do. 0 1 2 3<\/li>\n
  2. I get the most out of my talent and skills. 0 1 2 3<\/li>\n
  3. When a coach or manager tells me how to correct a mistake I\u2019ve
    \nmade, I tend to take it personally and feel upset. 0 1 2 3<\/li>\n
  4. When I am playing sports, I can focus my attention and block out distractions.
    \n0 1 2 3<\/li>\n
  5. I remain positive and enthusiastic during competition, no matter how
    \nbadly things are going. 0 1 2 3<\/li>\n
  6. I tend to play better under pressure because I think more clearly.
    \n0 1 2 3<\/li>\n
  7. I worry quite a bit about what others think about my performance. 0
    \n1 2 3<\/li>\n
  8. I tend to do lots of planning about how to reach my goals. 0 1 2 3<\/li>\n
  9. I feel confident that I will play well. 0 1 2 3<\/li>\n
  10. When a coach or manager criticizes me, I become upset rather than
    \nhelped. 0 1 2 3<\/li>\n
  11. It is easy for me to keep distracting thoughts from interfering with
    \nsomething I am watching or listening to. 0 1 2 3<\/li>\n
  12. I put a lot of pressure on myself by worrying how I will perform.
    \n0 1 2 3<\/li>\n
  13. I set my own performance goals for each practice. 0 1 2 3<\/li>\n
  14. I don\u2019t have to be pushed to practice or play hard; I give 100%.
    \n0 1 2 3<\/li>\n
  15. If a coach criticizes or yells at me, I correct the mistake without
    \ngetting upset about it. 0 1 2 3<\/li>\n
  16. I handle unexpected situations in my sport very well. 0 1 2 3<\/li>\n
  17. When things are going badly, I tell myself to keep calm, and this
    \nworks for me. 0 1 2 3<\/li>\n
  18. The more pressure there is during a game, the more I enjoy it. 0 1
    \n2 3<\/li>\n
  19. While competing, I worry about making mistakes or failing to come
    \nthrough. 0 1 2 3<\/li>\n
  20. I have my own game plan worked out in my head long before the game
    \nbegins. 0 1 2 3<\/li>\n
  21. When I feel myself getting too tense, I can quickly relax my body
    \nand calm myself. 0 1 2 3<\/li>\n
  22. To me, pressure situations are challenges that I welcome. 0 1 2 3<\/li>\n
  23. I think about and imagine what will happen if I fail or screw up.
    \n0 1 2 3<\/li>\n
  24. I maintain emotional control no matter how things are going for me.
    \n0 1 2 3<\/li>\n
  25. It is easy for me to direct my attention and focus on a single object
    \nor person. 0 1 2 3<\/li>\n
  26. When I fail to reach my goals, it makes me try even harder. 0 1 2
    \n3<\/li>\n
  27. I improve my skills by listening carefully to advice and instruction
    \nfrom coaches and managers. 0 1 2 3<\/li>\n
  28. I make fewer mistakes when the pressure\u2019s on because I concentrate
    \nbetter. 0 1 2 3<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"
    Submitted by: Sandy Kimbrough, Louisa DeBolt & Richard S. Balkin<\/div>\n

    Abstract<\/strong><\/p>\n

    The Athletic Coping Skill Inventory (ACSI-28) was completed by twenty-six
    \n collegiate baseball players. Performance statistics were collected, including
    \n batting average (BA), number of errors committed (ERR), and earned run
    \n average (ERA) for pitchers. Regression analysis was carried out using
    \n the seven areas of the ACSI-28 (peaking under pressure, freedom from worry,
    \n coping with adversity, concentration, goal setting and mental preparation,
    \n confidence and achievement motivation, and ‘coachability’)
    \n as the independent variables, and the current season’s performance
    \n statistics as the dependent variables. Correlation coefficients revealed
    \n significance between concentration, confidence, and ERA, while there were
    \n no significant relationships with BA or ERR and any of the psychological
    \n variables. Many of the psychological variables were highly related. While
    \n sequential linear regression did not reveal statistically significant
    \n relationships between the performance statistics and the psychological
    \n variables, large effect sizes indicated a strong degree of practical significance.
    \n Specifically, peaking under pressure and ‘coachability’ appeared
    \n to be strong predictor variables for ERA, concentration for ERR, and ‘coachability’
    \n for BA.<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_options":[]},"categories":[291,296],"tags":[27,76,77,8],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4btio-4a","jetpack-related-posts":[{"id":404,"url":"https:\/\/thesportjournal.org\/article\/coping-skills-and-self-efficacy-as-predictors-of-gymnastic-performance\/","url_meta":{"origin":258,"position":0},"title":"Coping Skills and Self-efficacy as Predictors of Gymnastic Performance","date":"January 19, 2011","format":false,"excerpt":"Garifallia Daroglou ### Abstract The purpose of this study was to examine the way that gymnastic performance can be discriminated based on psychological skills and self-efficacy. The sample of the study was 101 gymnasts (Mage = 11.8 \u00b1\u00ad.74 years, 22 male and 79 female), who competed at the Hellenic Championship\u2026","rel":"","context":"In "Sports Exercise Science"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":7914,"url":"https:\/\/thesportjournal.org\/article\/college-footballs-bottom-line-impact-exploring-the-relationship-of-football-performance-on-athletic-finances-for-division-i-institutions-today\/","url_meta":{"origin":258,"position":1},"title":"College Football\u2019s Bottom-Line Impact: Exploring the Relationship of Football Performance on Athletic Finances for Division I Institutions Today","date":"July 23, 2021","format":false,"excerpt":"Authors: Spencer D. Wyld1 and David C. Wyld2 1 Walton College of Business, Department of Finance, University of Arkansas, Fayetteville, AR, USA2 Department of Management & Business Administration, Southeastern Louisiana University, Hammond, LA, USA Corresponding Author:David C. Wyld, DBA47042 Scott DriveHammond, LA 70401dwyld@selu.edu985-789-2127 Spencer D. Wyld, M.B.A., is a doctoral\u2026","rel":"","context":"In "Research"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2021\/07\/Figure1.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":369,"url":"https:\/\/thesportjournal.org\/article\/investigation-of-recruiting-criteria-of-leading-ncaa-division-i-softball-coaches\/","url_meta":{"origin":258,"position":2},"title":"Investigation of Recruiting Criteria of Leading NCAA Division I Softball Coaches","date":"April 8, 2010","format":false,"excerpt":"Amber N. Kavekar, M.S., Trinity Valley Community College; Sally J. Ford, Ph. D, Texas Woman\u2019s University Abstract Purpose of this investigation was to determine the recruitment criteria of the 50 winningest active coaches in NCAA I collegiate softball. Twenty-seven of the NCAA Division I head coaches completed a survey designed\u2026","rel":"","context":"In "Sports Management"","img":{"alt_text":"Figure 1","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2010\/04\/Figure1.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":267,"url":"https:\/\/thesportjournal.org\/article\/african-americans-in-college-baseball\/","url_meta":{"origin":258,"position":3},"title":"African-Americans in College Baseball","date":"March 14, 2008","format":false,"excerpt":"Submitted by: Frank B. Butts, Laura M. Hatfield & Lance C. Hatfield Abstract: The under-representation of African-Americans in college baseball is evident. African-American athletes make up only 4.5% of all National Collegiate Athletic Association (NCAA) baseball players. They are a shrinking percentage of Major League Baseball players. 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Her research interests range\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"Ortiz LaGrange Table 1","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2006\/01\/Ortiz-LaGrange-Table-1-300x139.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":301,"url":"https:\/\/thesportjournal.org\/article\/relationship-of-selected-pre-nba-career-variables-to-nba-players-career-longevity\/","url_meta":{"origin":258,"position":5},"title":"Relationship of Selected Pre\u2013NBA Career Variables to NBA Players\u2019 Career Longevity","date":"April 2, 2008","format":false,"excerpt":"Submitted by: William Abrams, East Lansing, Michigan, John C. Barnes, University of New Mexico, Annie Clement, Ph. D., J.D., Saint Leo University Abstract Given the change in the business nature of the National Basketball Association (NBA), the player evaluation process has become increasingly important. 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