We present multiple candidate models for predicting angling effort from indices obtained from time lapse digital cameras.

Models account for excessive zeros common when only a proportion of the fishing area is monitored using cameras

We include a method for filling data gaps when cameras fail to collect data.

Selected model suggests that mean effort when camera detects no anglers is different between weekends/weekdays, as is the expansion when cameras do see effort.

Model addresses several shortcomings inherent when using cameras to predict angler effort.