This paper proposes a causal spatiotemporal convolutional network for real-time eye tracking with event cameras, designed for edge hardware through simple operations (convolutions, ReLU) and achieving greater than 90% activation sparsity via training regularisation. The model achieved 0.9916 p10 accuracy on the AIS 2024 event-based eye tracking Kaggle challenge.