-identity theory uses two important terms, “team identification” and “in-/out-group,” that help explain fans’ attitudes and behaviors in certain contexts. Team Identification and Player Identification Team identification in sport is considered “the personal commitment and emotional involvement customers have with
Sitong Guo, Andrew C. Billings, and James C. Abdallah
Shih-Hao Wu, Ching-Yi Daphne Tsai, and Chung-Chieh Hung
This study extends literature on the effects of fan identification on fan loyalty, and antecedents that trigger such effects. This study incorporates trust, a key relationship marketing construct, in the sport industry. The relationship between trust and two other critical antecedents of sport fan loyalty, identification and vicarious achievement motive, is examined from the perspectives of both fan-player and fan-team. The results show that antecedents from distinct perspectives influence loyalty differently. Team identification (fan-team level) is the major determinant of fans’ repatronage intention, with trust in the team as the key driver. However, player identification (fan-player level) has an indirect effect, which must go through team identification to repatronage intention. Therefore, sport organizations are recommended to invest a substantial part of their resources on activities that generate long-term effects, such as trust in the team and team identification, rather than on short-term strategies such as attracting star players.
Gregory R. Cox, Iñigo Mujika, and Cees-Rein van den Hoogenband
Water polo is an aquatic team sport that requires endurance, strength, power, swimming speed, agility, tactical awareness, and specific technical skills, including ball control. Unlike other team sports, few researchers have examined the nutritional habits of water polo athletes or potential dietary strategies that improve performance in water polo match play. Water polo players are typically well muscled, taller athletes; female players display higher levels of adiposity compared with their male counterparts. Positional differences exist: Center players are heavier and have higher body fat levels compared with perimeter players. Knowledge of the physical differences that exist among water polo players offers the advantage of player identification as well as individualizing nutrition strategies to optimize desired physique goals. Individual dietary counseling is warranted to ensure dietary adequacy, and in cases of physique manipulation. Performance in games and during quality workouts is likely to improve by adopting strategies that promote high carbohydrate availability, although research specific to water polo is lacking. A planned approach incorporating strategies to facilitate muscle glycogen refueling and muscle protein synthesis should be implemented following intensified training sessions and matches, particularly when short recovery times are scheduled. Although sweat losses of water polo players are less than what is reported for land-based athletes, specific knowledge allows for appropriate planning of carbohydrate intake strategies for match play and training. Postgame strategies to manage alcohol intake should be developed with input from the senior player group to minimize the negative consequences on recovery and player welfare.
Andrew A. Flatt, Jeff R. Allen, Clay M. Keith, Matthew W. Martinez, and Michael R. Esco
, the position × time interaction as a fixed effect, and player identification as a random effect. Tukey tests were used for post hoc analyzes. Hedges’ g effect size (ES) ± 95% confidence interval was used to determine standardized differences. 20 All time-related comparisons were made relative to PS
Craig Thomas, Helen Jones, Craig Whitworth-Turner, and Julien Louis
, and individual player identification was included as the random effect. Data are presented as mean (SD), mean difference and 95% confidence intervals or the median and interquartile range for the reporting of nonparametric tests. Cohen d was calculated for effect size where normality was met and was
Mitchell J. Henderson, Bryna C.R. Chrismas, Christopher J. Stevens, Aaron J. Coutts, and Lee Taylor
coefficient model). Peak Tc for all 3 games was included in the model as a dependent variable (outcome), and minutes played and all external load (GPS) variables (all 3 games combined) were separately entered as fixed effects (predictors). Using a random intercept and slope design, player identification was