This paper presents a comparison of different feature extraction methods for automatically recognizing soccer ball patterns through a probabilistic analysis. It contributes to investigate different well‐known feature extraction approaches applied in a soccer environment, in order to measure robustness accuracy and detection performances. This work, evaluating different methodologies, permits to select the one which achieves best performances in terms of detection rate and CPU processing time. The effectiveness of the different methodologies is demonstrated by a huge number of experiments on real ball examples under challenging conditions.