It is often important to understand a player's skill level when researching the effects of delay in computer games. Past research has generally taken at face value that players' selfassessment aligns with actual abilities, yet there is also some suggestion that females may under-assess their game skills compared with males of equal ability. This paper evaluates the efficacy of self-rated skill as an effective method of differentiating player performance by analyzing data gathered in 4 previous user studies. Analysis confirms that self-rated skill can be effective for differentiating actual performance on average, but that it is not predictive for individuals, and that while player performance is generally comparable across gender, very few male participants in the collected studies rated themselves at the lowest skill level on a five point scale, and no females at all self-rated at the highest. Finally, this study found no significant difference between the performance of players in the two lowest self-rated skill tiers, and none between players in the two highest. These findings suggest that having participants self-rate on a five point scale, but applying those ratings in three tiers, may be the most effective method for differentiating actual game performance by player skill level across gender.

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See also:

• Shengmei Liu, Mark Claypool, Bhuvana Devigere, Atsuo Kuwahara, and Jamie Sherman. 'Git Gud!' - Evaluation of Self-Rated Player Skill Compared to Actual Player Performance, Technical Report WPI-CS-TR-20-03, Computer Science Department, Worcester Polytechnic Institute, July 2020. Online at: ftp://ftp.cs.wpi.edu/pub/techreports/pdf/20-03.pdf