Athlete burnout is increasingly reported as impacting esports players' wellbeing and performance. This study investigated the psychometric properties of the Athlete Burnout Scale (ABO-S) within esports. Specifically focusing on item discrimination and difficulty parameters to establish optimal raw cut-off scores indicating levels of burnout risk among esports players. Participants were 453 English-speaking adult esports players who ranked in the top 40% of one of seven major esports. The sample included 372 males, 74 females, and seven nonbinary participants who represented 66 countries. Item Response Theory analysis, including Rasch and Graded Response Model, was used to examine the ABO-S's psychometric properties. The GRM provided a superior fit, with all items showing sufficient discrimination and difficulty levels. Items related to feeling wearied, lacking energy, and feeling physically drained demonstrated high levels of information and reliability across a range of burnout levels. A provisional diagnostic cut-off point of ≥ 63 (+2SD) was established, indicating a high risk of burnout, with 2% of participants exceeding this threshold. Furthermore, raw total burnout scores of ≥47 (+0.5SD) and 52 (+1SD) were also identified. The ABO-S is a robust instrument for assessing burnout in esports players, with specific items effectively identifying varying levels of burnout. The establishment of cut-off scores aids in identifying players at high risk of burnout, contributing to better support and intervention strategies in the esports community. These findings further the understanding of burnout in esports, highlighting the scale's utility in monitoring and addressing player wellbeing.