Emotion is a key factor in understanding user experiences (UX) of interactive systems. An emerging trend within HCI is to apply physiological sensors for uncovering emotions. Previous studies rely on various sophisticated analysis techniques and specialized knowledge to interpret sensor data. While commendable for increasing accuracy at fine grained latencies (to detect events within seconds), this can be challenging for UX practitioners without specialized knowledge. This study contributes in two ways. Firstly by understanding the level of sensor accuracy in detecting UX related events. Secondly by applying a basic analysis approach where sensor data is interpreted by 21 non specialist participants (no previous experience in doing this). Their performance is compared to random guessing. Findings show that sensor data analyzed by non-specialists are significantly more accurate in capturing subjectively reported UX events than random guessing. An accuracy level of 60-80% was obtained at granularities within 3.5-11 seconds of UX related events.