Like any other Internet of Things (IoT) communication solution, LoRaWAN is vulnerable to profiling attacks such as Denial of Service including reactive jamming or Man in The Middle attacks. These attacks can be challenging to detect and source-locate due to their brief occurrence when attempting to block or simulate a signal. Its deployment requires good accuracy on time predictability. This paper analyzes the temporal behavior of data packets that were captured in a real-world environment with LoRaWAN links over a 16-month period with more than 8 million frames. The aim is to provide tools for analyzing temporal predictability on LoRa data packets to enhance future secure designs. To achieve this, we propose some features and apply them to the dataset. The study reveals slight variations in behavior within the coverage area on a monthly basis, as well as the existence of easily predictable temporal patterns in some device transmissions. Additionally, our findings indicate that designing the LoRaWAN IoT system to transmit at pseudorandom intervals or avoiding static increments in the frame counter could mitigate the risk of time predictability.