This observational and exploratory study describes the agreement between peer assessments and professor assessments in two successive peer assessment workshops involving 96 second-year engineering students at the National School of Applied Sciences of Kenitra, part of Ibn Tofail University in Morocco. Equal-sized groups were formed based on student profiles using clustering and a balancing system. The first strategy aimed to maximise within-group profile similarity to form homogeneous groups by placing students from the same cluster in the same group, while the second aimed to maximise profile diversity to form heterogeneous groups by combining students from different clusters, subject to the available cluster sizes. For each workshop, we compared the average peer grade for each assignment with the professor’s grade using Pearson’s correlation, TOST equivalence tests, and Bland–Altman analysis. In the full samples, the first workshop showed a strong correlation (r = 0.90) and equivalence of means within the predefined ±4-point margin, whereas the second showed a weaker correlation (r = 0.43), a more negative mean bias, wider limits of agreement, and no equivalence of means within this margin. The ±4-point criterion relates to the mean difference and does not imply that acceptable agreement is established for every assignment. A sensitivity analysis restricted to assignments that received exactly four peer ratings supported the equivalence of means observed in both workshops, with mean differences of −0.2 and −0.4 points, respectively, whereas differences in correlation and dispersion persisted. The grouping strategy varied in conjunction with the task, the assessment grid, participation and the number of peer ratings, so its independent contribution cannot be determined. The inferential analyses did not account for dependence arising from shared assessors and groups, making the confidence intervals and conclusions regarding equivalence provisional. Controlled comparisons with simpler grouping methods are needed to determine whether profile-based grouping contributes to the quality of peer assessment.