1. A method to correct for temporal variability in incoming streams of media and data to optimize the performance of a pattern recognition system, comprising: receiving from one of said incoming streams a point in time when an event is announced; storing the point of time on a non-transitory media accessed by a processor programmed to transact the following remaining method steps; applying a probability distribution about the point in time calculated with a digital processor and stored in memory; shifting a point of highest probability of the probability distribution back in time by an amount effective to accommodate for a delay between the event and the announcement by copying stored values to a new address range that represents a shift in time; comparing a detected pattern of the event to a stored pattern of similar events and applying a confidence value to the comparison; and confirming to the pattern recognition system that the event occurred at the point of highest probability when the confidence score exceeds a predefined threshold.