Relationships Between Perfectionism, Training Load and Elite Junior Football Players’ Self-Assessed and Coach-Assessed Skills

Authors: Fredrik Klund & Stig Arve Sæther

Corresponding Author:
Stig Arve Sæther. Mr
Norwegian University of Science and Technology
Department of Sociology and Political Science,
Dragvoll, 7491 Trondheim, Norway
E-mail: stigarve@ntnu.no
00477-355-1133

Stig Arve Sæther are associate professor in sport science at the Norwegian University of Science and Technology. His research focusing mainly on talent development, youth sport and sport psychology related to high level performance.

Relationships Between Perfectionism, Training Load and Elite Junior Football Players’ Self-Assessed and Coach-Assessed Skills

ABSTRACT
The purpose of this study was to describe Norwegian elite junior football players’ perfectionism and training load assigned and self-imposed and examine how these factors were related to their own and their coaches’ assessments of their skills. The participants were 115 Norwegian junior football players (M age = 17.8 yrs, SD = .79 yrs) representing six professional football clubs at the two highest levels in Norway. Self-ratings on dimensions of perfectionism were highest for personal standards and lowest for perceived parental pressure. The players reported taking part in 6.2 organized weekly training sessions lasting a total of 10.6 hours and 2.1 weekly self-organized sessions lasting a total of 4.4 hours. Correlation analysis showed that coach-assessed player skills correlated positively with personal standards and frequency and duration of organized training but not independent training. Self-assessed player skills correlated positively personal standards and duration of self-organized training, but not with measures of organized training. T-tests comparing players with high and low coach-assessed skills showed that highly skilled players did more organized training, both in terms of frequency and duration of sessions, and reported higher personal standards. The less skilled players perceived higher pressure from parents and coaches. Overall the findings suggest that players’ ratings of their skills are related to the volume of self-organized training whereas coaches’ ratings are related to involvement in organized training sessions. Having higher personal standards was associated with volumes of both organized and independent training and coaches rated players with higher personal standards as more skilled. These findings indicate that personal standards are essential to skill development and coaches should encourage players to strive for high personal standards.

Keywords: Talent development, coach-assessed skills, perfectionism, training load, elite junior football players

INTRODUCTION
To become a professional even an extremely talented football player is dependent on several factors ‘going the right way’. Players have little influence over many of these factors, e.g. coach quality, selection, training facilities etc., yet they are expected to do their bit towards maximizing their chances of becoming a professional player. They are expected to be highly motivated, self-regulating (Toering, Elferink-Gemser, Jordet, & Visscher, 2009), have the right attitude (O´Connor, Larkin, & Williams, 2016; Sæther, 2014), mentally tough (Rodahl, Giske, Peters, & Høigaard, 2015) and able to cope with stress (Nicholls, 2011).

Players who belong to an elite junior football team associated with a professional club are operating in a highly competitive environment, where they are expected to be able to handle the pressure of performing and being compared to their teammates, since often only one or two of them are expected to succeed. One would therefore expect that players who are going to succeed will do or sacrifice that little bit extra in order to increase their chances of making the grade. This may manifest in motivation, self-regulation, attitudes and mental toughness, but the ultimate way of demonstrating commitment to one’s future as a footballer is probably be through involvement in training, both in terms of total duration and frequency of sessions. Ericsson, Krampe, and Tesch-Römer (Ericsson, Krampe, & Tesch-Römer, 1993) argued that one would expect to find a direct relationship between training load and performance. Although one would expect training volume to influence a player’s chance of becoming a professional, research has shown that it does not predict success (Haugaasen, Toering, & Jordet, 2014; Sæther, 2017b). The content of training is as important as the volume. Players who do high volumes of high-quality training increase their chance of later success. Perfectionism may therefore be an asset, since many coaches would expect the players to be perfectionists.

Having high standards is essential to talent development, but perfectionism is a personality construct that has been associated with several types of maladjustments. Frost, Marten, Lahart, and Rosenblate (Frost, Marten, Lahart, & Rosenblate, 1990) described perfectionism as a tendency to set unrealistically high standards of performance; this is what distinguishes perfectionists from those who are highly competent and successful. Hamacheck (Hamachek, 1978) drew a distinction between normal (adaptive) and neurotic (maladaptive) perfectionism, arguing that perfectionism is a two-dimensional concept. Adaptive perfectionism involves having high personal standards of achievement, getting pleasure from getting the work done, yet being capable of choosing imperfect solutions in certain situations. Adaptive perfectionists will exert maximum effort in pursuit of their standards, but are able to accept that personal limitations and environmental obstacles may prevent them achieving their ideal performance (Dunn, Causgrove Dunn, & Syrotuik, 2002). Adaptive perfectionism is self-referenced and therefor they set high personal standards without reference to external factors such as pressure from coaches and parents, whereas maladaptive perfectionists are characterized by an overwhelming fear of failure. Both adaptive and maladaptive perfectionists set high performance standards, but the crucial difference is that maladaptive perfectionists tend to be overly critical of themselves (Frost et al., 1990) and infrequently satisfied with their performance, because of their lack of freedom to make mistakes (Dunn et al., 2002). Previous research on talented athletes has found that adaptive perfectionism is more prevalent than maladaptive perfectionism (Dunn, Gotwals, Dunn, & Syrotuik, 2006; Nerland & Sæther, 2016).

An essential part of talent development is the training loads talented players are dependent of conducting to be able to become a professional football player. Earlier studies on elite junior football players in the UK, Denmark, the Netherlands, Sweden, and Portugal have shown that 15- to 16-year-olds do 6.1 10.2 hours of organized training per week and 17- to 19-year-olds do 8.3 12.2 hours (Baxter-Jones & Helms, 1996; Christensen, Laursen, & Sørensen, 2011; Elferink-Gemser, Huijgen, Coelho-e-Silva, Lemmink, & Visscher, 2012; Ivarsson, Stenling, Fallby, Johnson, & Borg, 2015; Malina et al., 2000; McMillan et al., 2005; Sæther, 2017b). Fewer studies have looked at self-organized training, but a Dutch study reported that U16 U19 players trained independently for 2.5 hours a week (Elferink-Gemser et al., 2012), a Swedish study reported that U13 U16 players trained independently for 3.8 hours a week (Ivarsson et al., 2015) and a Norwegian study reported that U16-U19 players trained independently for 3–4.5 hours a week (Sæther, 2017b). A major limitation of studies on training load is the variance in the scales used, but another limitation is the inconsistency in the types of training that are included; some include school activity whereas others do not.

Talented football players are used to being assessed by their coaches on a regular basis, but there has been little research on the criteria coaches use to identify talent. Larkin and O’Connor (Larkin & O´Connor, 2017) found that Australian U13 coaches considered technical, tactical and psychological attributes most important, and physiological, anthropometric and sociological attributes less important. A study of Norwegian youth players showed that compared with lower-level players, the top-level players thought that their club coaches accorded mental skills greater importance (Matin & Sæther, 2017). Independent of their coaches, players are dependent on the ability to assess their own skills and abilities (Kannekens, Elferink-Gemser, Post, & Visscher, 2009), even if they constantly are assessed by their coaches. One of the few studies in which talented players have been asked to compare their skills to those of their teammates found that players tend to overrate their own skills (Nerland & Sæther, 2016). Matin and Sæther (Matin & Sæther, 2017) showed that top-level players considered themselves to have better technical and tactical skills than low-level players.

This study was based on perfectionism theory and the training load literature; its purpose was to describe Norwegian elite junior football players’ perfectionism and training load both organized and independent and to examine how these factors were related to their own and their coaches’ assessments of their skills.

METHOD
Participants
One hundred and fifteen male Norwegian junior football players (mean age = 17.8 yrs, SD = .79 yrs) representing six professional football clubs three top-level clubs (52.2%) and three league two clubs (47.8%) took part in the study.

Procedure
The data were collected after a training session at the players’ clubs, at start of their season. Before participants completed the questionnaire they were told the purpose of the study and informed that their participation was voluntary and would be anonymous, and that all information would be treated confidentially. The study was approved by the Norwegian Social Science Data Services and carried out in accordance.

Measures
Perfectionism. The Multidimensional Perfectionism Football Scale (MPS-Football; (Dunn et al., 2002)) was used to assess athletes’ perfectionism. The MPS-Football is a 34-item scale organized into subscales: personal standards (7 items, e.g. “I hate being less than the best at things in football”; Cronbach’s alpha = .772), concern over mistakes (8 items, e.g. “When I fail even slightly in competition, for me, it is as bad as being a complete failure”; Cronbach’s alpha = .775), perceived parental pressure (9 items, e.g. “My parents set very high standards for me in football”; Cronbach’s alpha = .844), perceived coach pressure (6 items; e.g. “I feel like I can never quite live up to my coach’s standards”; Cronbach’s alpha = .674) and doubts about actions (4 items, e.g. “I tend to get behind in my work because I repeat things over and over”; Cronbach’s alpha = .560). We excluded the doubts about actions items from analysis because of concerns about this subscale’s validity, amongst other things (Dunn et al., 2002). Responses were given on a five-point Likert scale ranging from 1 = not at all true to 5 = completely true.

Training volume. We did not use a standardized instrument to collect data on training volume. Players were asked to report their weekly number of organized sessions in the previous season using a seven-point scale ranging from 1 = one session to 7 = seven or more, and to report the number of hours of training this had involved. Players were also asked to report the number of times they had trained independently each week, using the following response scale: 1 = none; 2 = once; 3 = 2–3 times; 4 = 4–5 times; 5 = 6–7 times, and the total number of hours they had spent doing independent training. Although this method has not been standardized it has been used previously with similar groups of elite junior players (Sæther, 2017a, 2017b; Sæther & Aspvik, 2016).

Coaches’ assessment of players’ skill level. Unlike perfectionism, coaches’ perceptions of players’ skill were not captured using a standardized instrument. Coaches were asked to assess six specific skills (speed, endurance, strength, technical skills, tactical skills and mental skills), overall skills and talent. The coaches were asked to assess the skills of the players in the elite club, on a scale from 1 = player with the weakest skills in the age cohort, to 10 = player with the best skills in the age cohort. As a preliminary to principle component analysis (PCA) of the data (carried out using Stata) we assessed their suitability for factor analysis. Inspection of the correlation matrix revealed the presence of many coefficients of .3 and above. The Keiser-Meyer-Olkin value was .89, exceeding the recommended threshold of .6, and Bartlett’s test of Sphericity reached statistical significance (p < .05), supporting the factorability of the correlation matrix (Tabachnick, 2001). The average of scores for the eight items was used as an index of coaches’ assessment of they player’s skill (Cronbach’s alpha = .934).

Players’ assessments of their own skills. The instrument to capture players’ self-assessments of skill is not a standardized instrument, but has been used in some earlier studies of similar groups of elite junior players (Nerland & Sæther, 2016; Sæther, Aspvik, & Høigaard, Accepted). The instrument is based on the operationalization of four facets of talent in soccer (physical, physiological, sociological and psychological) by Williams and Reilly (Williams & Reilly, 2000). Sæther (Sæther, 2014) have used the following four skills in a previous study; technical, tactical, mental, social and physical abilities. In this study participants were asked to compare their technical, tactical, mental and physical abilities to those of other players in their club using the following response options: 1 = worse than most; 3 = about average; 5 = better than most. The sum of scores for the four variables was used as an index of self-assessed player skill (Cronbach’s alpha = .406).

Data Analysis
The data were screened for missing values, potential outliers, and violations of normality. Sample means were computed for all the scales. Descriptive statistics, Pearson product-moment correlation coefficients and the results of Student’s t-tests are presented in the Results. Information about scales’ reliability is presented above as part of the Materials and Methods section.

RESULTS
Table 1 presents descriptive statistics for the variables. On average the coaches assessed players as better than average, just as, on average, players considered their own skills to be better than those of most of their club peers. Personal standards and perceived parental pressure attracted respectively the highest and lowest scores of all the perfectionism dimensions. Players reported taking part in 6.2 organized training sessions per week, amounting to a total of 10.6 hours of organized training, and training independently 2.1 times per week, amounting to a total of 4.4 hours of independent training.

Table 1

Correlation coefficients are reported in Table 2. Coach-assessed player skills were positively correlated with frequency (p < .01) and duration (p < .05) of organized training, and with personal standards (p < .05), but not with frequency or duration of independent training. Self-assessed player skills were positively correlated with frequency of independent training (p < .05) and with personal standards (p < .01), but not with frequency or duration of organized training. Personal standards were also correlated positively with both frequency (p < .05) and duration (p < .01) of organized training, but not with frequency or duration of independent training. Table 2

The results of independent-samples Student’s t-tests are presented in Table 3. Players rated as highly skilled by coaches took part in more organized training, both in terms of frequency of sessions and duration (p < .01), and also reported higher personal standards (p < .05). The less skilled players perceived greater parental pressure (p < .05) and greater coach pressure (p < .05). Table 3

DISCUSSION
Talented football players are expected to do their bit to increase their chances of becoming professional and are therefore expected to be able to cope with pressure, stress and high expectations. This suggests that perfectionism may be an asset in the elite sports environment; however Frost et al (Frost et al., 1990) defined perfectionism as a tendency to set unrealistically high standards of performance and focused on the disadvantages of perfectionism, especially maladaptive perfectionism. Our sample of elite junior players scored highest on the personal standards dimension of perfectionism, the only adaptive dimension, and lowest on perceived parental pressure. This suggests that they have high personal standards of achievement, yet they are also capable of adapting and are capably of coping with “imperfect” solutions in certain situations. The perceived lack of parental pressure may indicate that these players have been exposed to a mastery motivational climate (Ommundsen, Roberts, Lemyre, & Miller, 2005).

Compared with earlier studies of both organized (Baxter-Jones & Helms, 1996; Christensen et al., 2011; Elferink-Gemser et al., 2012; Ivarsson et al., 2015; Malina et al., 2000; McMillan et al., 2005; Sæther, 2017b) and independent (Elferink-Gemser et al., 2012; Ivarsson et al., 2015; Sæther, 2017b) training sessions, our players report a high frequency and duration of training. These results may explain why both the coaches and players assessed the players’ skills as above average, as earlier studies also have found (Nerland & Sæther, 2016). It is natural that the players whom the coaches regard as most skilled get the most opportunities to participate in organized training sessions.

Even though both training load and perfectionism solely could be essential part of talent development, their relationship could be regarded as more important. The results indicate that the coaches and players’ assessment of players’ skills are related to involvement in different forms of training. Coaches’ assessments of skill were correlated with the frequency (p < .01) and duration (p < .05) of a player’s organized training, whereas players’ assessments of their skill were positively correlated with the frequency of their independent training (p < .05). A potential explanation for this is that players connect their skills to their investment in independent training, whereas coaches’ connect players’ skill to participation in organized sessions; thus both players and coaches attribute most importance to their own contribution to the development of skill. Both coaches’ and players’ assessments were positively correlated with players’ personal standards (Dunn, Causgrove Dunn, et al., 2006; Nerland & Sæther, 2016). Personal standards were positively correlated with the frequency (p < .05) and duration (p < .01) of organized training but not independent training. It should be noted, however, that our index of self-assessed skill had low reliability and this may have affected our results.

Talent identification is an essential activity for most top clubs and furthermore the skills regarded most likely to predict future players at the elite level. Our results suggest that the players that coaches consider least skilled feel the most pressure to succeed. This group of players reported lower personal standards, but perceived greater pressure from both parents (p < .05) and coaches (p < .05). It is naturally to assume that these players are feeling the pressure. Interestingly, the least skilled players were given less opportunities to catch up with the best players since they trained significantly less organized training sessions both in terms of number and hours. These results corroborate earlier studies of elite junior football players that showed that players with the lowest volumes of playing time reported more evaluation and performance stress (Sæther & Aspvik, 2016). Although there were only small differences between the skilled and less skilled players in our sample with respect to parental and coach pressure, both parents and coaches should be aware of their impact on the players. Especially the least skilled players could get a double negative impact from their coaches and parents if they get more pressure and are more stressed regarding their development as football players.

CONCLUSION
Overall the findings suggest that players’ ratings of their skills are related to the volume of self-organized training whereas coaches’ ratings are related to involvement in organized training sessions. Having higher personal standards was associated with volumes of both organized and independent training and coaches rated players with higher personal standards as more skilled. These findings indicate that personal standards are essential to skill development and coaches should encourage players to strive for high personal standards.

ACKNOWLEDGMENTS
None

REFERENCES
1. Baxter-Jones, A. D. G., & Helms, P. J. (1996). Effects of training at a young age: A review of the Training of Young Athletes (TOYA) study. Pediatric Exercise Science(8), 310-327.
2. Christensen, M. K., Laursen, D. N., & Sørensen, J. K. (2011). Situated learning in youth elite football: a Danish case study among talented male under-18 football players. Physical Education and Sport Pedagogy, 16(2), 163-178.
3. Dunn, J. G. H., Causgrove Dunn, J., Gotwals, J. K., Vallence, J. K. H., Craft, J. M., & Syrotuik, D. G. (2006). Establishing construct validity evidence for the Sport Multidimensional Perfectionism Scale. Psychology of Sport and Exercise, 7, 57-79.
4. Dunn, J. G. H., Causgrove Dunn, J., & Syrotuik, D. G. (2002). Relationship Between Multidimensional Perfectionism and Goal Orientations in Sport. Journal of Sport & Exercise Psychology, 24(4), 376-395.
5. Dunn, J. G. H., Gotwals, J. K., Dunn, J. C., & Syrotuik, D. G. (2006). Examining the relationship between perfectionism and trait anger in competetive sport. International Journal of Sport and Exercise Psychology, 4(1), 7-24.
6. Elferink-Gemser, M. T., Huijgen, B. C., Coelho-e-Silva, M., Lemmink, K. A., & Visscher, C. (2012). The changing characteristics of talented soccer players – a decade of work in Groningen. Journal of Sports Sciences, 30(15), 1581-1591.
7. Ericsson, K. A., Krampe, R., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406.
8. Frost, R. O., Marten, P., Lahart, C., & Rosenblate, R. (1990). The Dimensions of Perfectionism. Cognitive Therapy and Research, 14(5), 449-468.
9. Hamachek, D. E. (1978). Psychodynamics of normal and neurotic perfectionism (Vol. 15).
10. Haugaasen, M., Toering, T., & Jordet, G. (2014). From childhood to senior professional football: A multi-level approach to elite youth football players´ engagement in football-spesific activities. Psychology of Sport & Exercise, 15(4), 336-344.
11. Ivarsson, A., Stenling, A., Fallby, J., Johnson, U., & Borg, E., & Johansson, G. (2015). The predictive ability of the talent development environment on youth elite football players’ well-being: A person-centered approach. Psychology of Sport and Exercise, 16, 15-23.
12. Kannekens, R., Elferink-Gemser, M. T., Post, W. J., & Visscher, C. (2009). Self-Assessed tactical skills in elite youth soccer players: A longitudinal study. Perceptual and Motor Skills(109), 459-472.
13. Larkin, P., & O´Connor, D. (2017). Talent identification and recruitment in youth soccer: Recruiter¨s perceptions of the key attributes for player recruitment. PLOS one, 1-15.
14. Malina, R. M., Pena Reyes, M. E., Eisenmann, J. C., Horta, L., Rodrigues, J., & Miller, R. (2000). Height, mass and skeletal maturity of elite Portuguese soccer players aged 11-16 years. J Sports Sci, 18(9), 685-693. doi:10.1080/02640410050120069
15. Matin, V., & Sæther, S. A. (2017). Talented high school football players’ perception of talent identification criteria. Sport Mont Journal(2), 3-7.
16. McMillan, K., Helgerud, J., Grant, S. J., Newell, J., Wilson, J., Macdonald, R., & Hoff, J. (2005). Lactate threshold responses to a season of professional British youth soccer. Br J Sports Med, 39(7), 432-436. doi:10.1136/bjsm.2004.012260
17. Nerland, E., & Sæther, S. A. (2016). Norwegian football academy players – Players self-assessed competence, Perfectionism, Goal orientations and Motivational climate. Sport Mont Journal, 2, 7-11.
18. Nicholls, A. R. (2011). Mental toughness and coping in sport. In D. F. Gucciardi & S. Gordon (Eds.), Mental Tougness in Sport (pp. 30-46). New York: Routledge.
19. O´Connor, D., Larkin, P., & Williams, A. M. (2016). Talent identification and selection in elite youth football: An Australian context. European Journal of Sport Science, 16(7), 837-844.
20. Ommundsen, Y., Roberts, G. C., Lemyre, P.-N., & Miller, B. W. (2005). Peer relationships in adolescent competitive soccer: Associations to perceived motivational climate, achievement goals and perfectionism. Journal of Sports Sciences, 23(9), 977-989.
21. Rodahl, S., Giske, R., Peters, D. M., & Høigaard, R. (2015). Satisfaction with the coach and mental toughness in elite male ice hockey players. Journal of Sport Behavior, 38, 419-431.
22. Sæther, S. A. (2014). Talent identification in Soccer. What do Coaches Look for? Downloaded from: http://idrottsforum.org/sather140319/.
23. Sæther, S. A. (2017a). Characteristics of Professional and Non-Professional Football Players – An Eight-Year Follow-Up of Three Age Cohorts. Montenegrin Journal of Sports Science and Medicine(2), 13-18.
24. Sæther, S. A. (2017b). De norske fotballtalentene. Hvem lykkes og hvorfor? Oslo: Universitetsforlaget.
25. Sæther, S. A., & Aspvik, N. P. (2016). Norwegian Junior Football Players – Player ́S Perception Of Stress According To Playing Time. Sport Science Review, XXV(1-2), 85-96.
26. Sæther, S. A., Aspvik, N. P., & Høigaard, R. (Accepted). Norwegian football academy players – players’ characteristics, stress and coach-athlete relationship. The Open Sports sciences Journal.
27. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics: Boston: Allyn and Bacon.
28. Toering, T. T., Elferink-Gemser, M. T., Jordet, G., & Visscher, C. (2009). Self-regulated and performance level of elite and non-elite youth soccer players. Journal of Sports Sciences, 27(14), 1509-1517.
29. Williams, A. M., & Reilly, T. (2000). Talent identification and development in soccer. Journal of Sports Sciences, 18(9), 657-667.

Comparison of Laboratory and Field-Based Predictors of 5-km Race Performance in Division I Cross-Country Runners

Authors: Katie M. Sell, Ph.D., CSCS, TSAC-F, ACSM EP-C
Department of Health Professions, Hofstra University, NY
Jamie Ghigiarelli, Ph.D., CSCS, USAW, CISSN
Department of Health Professions, Hofstra University, NY

Corresponding Author:
Katie M. Sell, Ph.D., CSCS, TSAC-F, ACSM EP-C
Department of Health Professions, 101 Hofstra Dome, 220 Hofstra University, Hempstead, NY 11549
Phone: 516-463-5814
Email: Katie.Sell@hofstra.edu

Comparison of Laboratory and Field-Based Predictors of 5-km Race Performance in Division I Cross-Country Runners

ABSTRACT
Purpose: The purpose of this study was to examine the predictive capabilities of laboratory- (VO2max, VO2@VT) versus field-based performance variables (2-mile trial time; 2-MTT) in determining 5-km performance time in collegiate cross-country runners. Methods: Twenty Division I college cross-country runners completed a 2-MTT on an outdoor track, a VO2max test under controlled laboratory settings, and a 5-km run under competitive conditions. All tests were completed within a 10-day timeframe. Oxygen uptake during the VO2max test was measured during treadmill running using open circuit spirometry. Oxygen consumption at ventilatory threshold (VO2@VT) was determined using the ventilatory equivalent method. Results: Significant correlations were observed between each predictor variable and 5-km performance time. Regression analyses revealed that 2-MTT and VO2@VT contributed significantly to predicting 5-km race performance (r2 = 0.90, p<0.05). Conclusions: For the highly trained runners in this study, 2-MTT and VO2@VT are among the variables best able to predict 5-km race performance, and accounted for a similar magnitude of variance in 5-km performance time. Applications in Sport: A 2-MTT is cheaper, quicker, and more feasible to administer than a VO2max test to determine VT during the short pre-season and intensive in-season inherent in collegiate cross-country schedules. Given the results of this study, the 2-MTT may present an attractive alternative to laboratory testing as a means to monitor cross-country runner’s progress throughout a season.
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Investigating the Relationship between Emotional Intelligence, Involvement in Collegiate Sport, and Academic Performance

Authors:
Urska Dobersek & Denise L. Arellano

Corresponding Author:
Urska Dobersek, Ph.D.
Department of Psychology
University of Southern Indiana
8600 University Blvd.
Evansville, IN 47712
Phone: (337) 853-7237
Email: udobersek@usi.edu

Biography:
Urska Dobersek is an Assistant Professor in the Psychology Department at University of Southern Indiana. Denise L. Arellano is an Instructional Designer at the University of Dallas.

Investigating the Relationship between Emotional Intelligence, Involvement in Collegiate Sport, and Academic Performance

ABSTRACT
The purpose of this study was to investigate the relationship between student-athletes and non-athletes on emotional intelligence (EI), and whether or not the involvement in collegiate sports moderates the relationship between EI and academic achievement as measured by the grade point average (GPA). An independent-samples t-test revealed that non-athletes were more empathetic than student-athletes; no other dimensions of EI (i.e., utilization of feelings, handling relationships, self-control) were significant. A hierarchical regression analysis suggested no moderation effects as evidenced by the interaction term explaining an additional 1.9% of the total variance. After removing the interaction terms, the model indicated a positive relationship between empathy, self-confidence, and academic performance. Additionally, student-athletes demonstrated a higher GPA compared to non-athletes. Some findings of the current study are incongruent with the previous research suggesting the need for the further research on EI.
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What Delivers an Improved Season in Men’s College Soccer? The Relative Effects of Shots, Attacking and Defending Scoring Efficiency on Year-to-Year Change in Season Win Percentage

Authors: Louis R. Joslyn, Nicholas J. Joslyn and Mark R. Joslyn

Corresponding Author:
Mark R. Joslyn, PhD.
1541 Lilac Lane
Lawrence, KS 66045-3129
mjoz@ku.edu
785-864-9046

Mark Joslyn is a political scientist and graduate director at University of Kansas.
Louis Joslyn is a graduate student at University of Michigan in Bioinformatics
Nicholas Joslyn is a student at Simpson College majoring in Mathematics and Physics.

ABSTRACT
In NCAA division 1 men’s college soccer, what performance measures determine improvement in win percentage from one season to the next? Though systematic research of college soccer is uncommon, using available team box scores we were able to construct robust models for year-to-year improvement in win percentage. For teams that improved win percentage greater than 5%, attacking efficiency – ratio of goals scored and shots taken – was the most important predictor followed by defending scoring efficiency – ratio of goals against and shots against – and total shots ratio – total shots for versus total shots against. We also find that efficiency measures are the most difficult to repeat from one season to the next. In short, the key performance measure for improved team win percentages is converting chances into goals, the most challenging team variable to sustain across seasons.
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The Leadership Techniques and Practices of Elite Collegiate Strength and Conditioning

Authors: Mike Voight, Ann Hickey, Michael Piper

Corresponding Author:
Mike Voight, Ph.D.
PEHP Department
Central Connecticut State University
1615 Stanley Drive
New Britain, CT 06050

Dr. Mike Voight is a professor in the Physical Education and Human Performance Department at Central Connecticut State University where he teaches graduate courses in leadership, sport psychology, and sport sociology. His email is voightmir@ccsu.edu, and his website is www.drvleads.com

Dr. Ann Hickey is an associate professor at Whittier College (CA) where she teaches sport psychology.

Michael Piper is assistant strength coach at Central Connecticut State University.

ABSTRACT
Leadership development has been given more attention in the field of strength and conditioning. Particular topics of interest have included how important a training ground and learning laboratory the university strength and conditioning space is for leadership development, the styles of leadership among strength coaches, leadership behavior, roles, job responsibilities and analyses of NCAA Division 1 strength and conditioning coaches, becoming a more valuable asset to the athletic program, and improving buy-in and leadership (Brooks, Ziatz, Johnson & Hollander, 2000; Feldman, 2013; Magnusen, 2010; Massey, Vincent, & Maneval, 2004; Voight, 2014).

The purpose of this investigation was to interview elite strength and conditioning coaches on their use of “best practices” leadership techniques and practices designed to improve player motivation, communication, commitment, and personal/team leadership. To this objective, participants were not only asked about their use of leadership techniques, but what they do to improve the leadership skills of whom they lead. This study used a semi-structured, exploratory interview design, which revealed numerous subthemes which fit into four major themes: leadership behaviors, leadership development, motivational techniques (buy-in), and relationships-communication. Results of this study can be used by current and up-and-coming strength and conditioning professionals to get the most from their own leadership skill sets as well as developing leadership among the teams they train.
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