The Use and Effect of Statistics in U.S. Professional Sports Leagues’ X Posts on Engagement, Enjoyment, and Emotion

This study examines the use and effect of statistics in online social media posts on X (formerly Twitter) for the top five professional sports leagues in the U.S. (NFL, NBA, MLB, MLS, and NHL) during 2023 for changes in engagement, enjoyment, and emotion. This study utilizes machine learning to code 49,455 X posts before employing AI-powered sentiment and emotion analysis tools, in conjunction with more traditional measures of engagement and enjoyment, of 136,401 mentions responding to a randomly sampled subset of 500 of these posts (50 with statistics and 50 without statistics present in each of the five leagues). First, findings revealed discrepancies in frequency of use of statistics across leagues. Next, while posts with statistics increased engagement, they also negatively impacted enjoyment. Finally, analysis revealed posts with statistics yielded more “sad” responses compared to more “joyful” responses to posts without statistics. However, results varied by sports league. Implications for exemplification theory and future sport communication research on the use of statistics in sports media and practical considerations for sports media professionals are discussed.