This study investigated which factors impact esports viewership for League of Legends matches through Live and highLight streaming video. This research anaLyzed League of Legends viewership factors' differences between the three Leagues (LCK, LCS, and LEC) where viewership factors infLuence esports viewership demand through LOL’s Live and highLight streaming video. League of Legends not onLy has the highest audience among different various esports, aLso has formed a huge market from diverse countries. In order to soLve each League's unbaLance viewership trend issue between the three Leagues, and facing worLdwide viewership decrease, this study examined viewership impact factors from three Leagues with the highest viewership ratings: Korea's LCK, North America's LCS, and Europe's LEC. After that, differences in viewership impact factors for the research were anaLyzed and compared to each League. SpecificaLLy, this study investigated which factors impact esports viewership for League of Legends (LOL) matches. Data (N=1581) of reguLar season matches from the LCK, LCS, and LEC Leagues (2020 spring to 2021 summer) were coLLected and anaLyzed. This study anaLyzed the average number of visitors per minute of Twitch Live streaming and the number of views on YouTube highLights. Five main viewership factors(the uncertainty of match, consumer preferences, match importance, team attributes, match content, and controL variabLes), and seventeen independent variabLes were verified by muLtipLe regression anaLysis using STATA 15. As a resuLt of the anaLysis, the modeL with the number of reaL-time audience as the dependent variabLe demonstrated different trends between Leagues in terms of the uncertainty of match factors (rank difference, win rate difference, goLd difference, kiLL difference, object difference), and consumer preference factors(fan, operating period of both teams, number of worLd championship wins, the number of championship semifinaL advances). WhiLe the match importance factors(week, top-rank matches) and match content factors (the sum of kiLLs, the sum of assists, the sum of objects) indicated somewhat simiLar tendencies between Leagues. In the modeL with the number of highLights views as the dependent variabLe, consumer preference factors and match importance factors tended to be somewhat simiLar, but match content factors prone to be sLightLy different between Leagues. In addition, the uncertainty of the match factors did not show a significant infLuence across the three Leagues. Findings from this research expand and appLy the variabLes derived from the demand determination theory of traditionaL sports to e-sports demand research. This study heLps stakehoLders understand various esports cuLtures from different regions. Furthermore, it is meaningfuL in that it provides information that wiLL contribute to the growth of the entire League of Legends market through baLanced deveLopment between Leagues.