The on-going technical progress in pervasive computing influences our daily activities more and more. In sports, smartphone apps are used to support athletes during training - either by giving plain physiological or motivating feedback. The Mobile Motion Advisor (MMA) is such kind of system, developed for the use in school children`s physical education. A school class resembles a highly inhomogeneous group regarding their physical fitness. Hence, considering absolute performance parameters might not be an appropriate way to grade the school children`s efforts. With the introduction of the relative Activity Index (rAI), we propose a method that approaches fair grading based on the technologies of the MMA. The rAI is a calculated value that resembles the relative activity of an individual within a group, based on the number of steps of each individual. As we found out, rAI correlates significantly (r = 0.620, p < 0.01) with the V02max which allows to deduce an estimated individual rAIestm. Comparing the estimated rAIest with the actual rAIm may enable us to grade efforts within the context of the games dynamics and the individual fitness.
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