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The efficient execution of surgical operations plays a crucial role in optimizing patient outcomes, evidencing the need for effective training methods to improve surgical skills. Medical training simulators, praised for objective, automated skill assessment, require instrumented sensors and relevant metrics for targeted feedback on important aspects of a surgical procedure. Traditional metrics that capture a single instance of force, such as peak or range, lack the characterization of the entire force profile and lose subtleties that may limit accurate evaluation of the skilled application of force, a valuable aspect of assessment in surgery. This study introduces novel force metrics inspired by motion smoothness-based measures, analyzed on an extensive dataset of 97 subjects suturing on an open vascular suturing simulator. We validated the effectiveness of these metrics by comparing the metric scores for subjects with different skill levels. Our findings highlight the value of these advanced force metrics as robust indicators of suturing performance, demonstrating their valuable potential for more accurate and objective skill assessment in surgical training.