The greatest cricket batsman – Sir Donald Bradman – used a batting technique that fans loved, but some critics slammed. A critical component was his lateral batting backlift technique. Highly successful batters use it to this day. Artificial Intelligence (AI) can now distinguish batters with a straight backlift from those using a lateral backlift, using video only. How AI spots legendary cricket batting back-lift using video footage
Researchers from the University of Johannesburg (UJ) built the first deep learning computer vision AI model to do this. Their research is published in Nature Scientific Reports. In future, coaches may give more detailed feedback to players using such technology. Or more easily identify players with lateral backlift components. Legendary technique In that split second just before a cricket bowler releases a ball at the crease, the batter initiates a very subtle movement. This is when the batter starts moving their bat into position. They select it depending
on the format of the game and the type of bowler approaching them. Most fast bowlers tend to bowl at between 140 and 150 km/h (87 to 93 mph), says Prof Habib Noorbhai. Noorbhai is currently Director of the Biomedical Engineering and Healthcare Technology (BEAHT) Research Centre at the University of Johannesburg (UJ). He is also a sports scientist and has worked with local and international cricket teams since 2010. His doctoral thesis was the first research to theorise the lateral batting backlift technique in cricket. Another factor is the batter’s instincts and training. Will they
bring up the bat straight with its face towards the ground or the stumps? Or will they angle the face of the bat outward towards second slip or the wicket keeper? This is the technique legendary batter Sir Donald Bradman used. Successful Test cricket batters also use it to this day. AI helping coaches The researchers – Mr Tevin Moodley, Prof Dustin van der Haar and Prof Habib Noorbhai – all played cricket at school. Moodley is a doctoral student and Van der Haar a pattern recognition
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