Comparing experts to amateurs in tennis, experts knew what would happen with the direction of a tennis serve roughly a third of a second earlier.
What separated the pros from everyone else was the ability to pull directional information out of the early stages of a swing and therefore to predict a split second earlier where to head. This fraction of time is game- changing. A serve going 120 miles per hour takes approximately a third of a second to travel the 60 feet from baseline to service line. This means that an expert, who doesn’t have to wait until contact, has twice as long to move, plant his feet, and swing.
Proving that anticipation mattered was one thing. The big question was, could it be taught? Farrow wanted to try, but he would be careful to not make the same mistake he had made with himself. He instructed some of the players from each group not to worry about predicting the direction of the serve but, instead, to focus on estimating its speed. The exercise was intended to force receivers to notice things like the angle of the racket head and the twist of a server’s shoulders relative to his hips — all kinematic cues that also contribute to a serve’s direction. Best of all, the connections would happen unconsciously. “It’s called implicit learning,” Farrow says. “We’re getting them used to watching for the right stuff, things like more-spin-equals-less-speed, but they don’t even know that they’re doing it.”
Farrow then tested the speed-prediction group against one that had been traditionally coached on service returns and another control group that had received no coaching. At the end of the day, the players who’d been told to predict the ball’s speed showed a small but significant improvement, anticipating the serve correctly an extra 5 percent of the time. More startling: The traditionally coached group didn’t improve at all.
Farrow has turned into a one-man band of perceptual training, transferring his tennis experience to volleyball, basketball, cricket, and other sports. It’s the culmination of an idea that originated 50 years ago, when a psychologist named Clarence Damron flashed slides of defensive plays at high school football players and then tested their ability to identify the maneuvers from the sidelines. Students who had watched the slides were better at guessing correctly, leading Damron to conclude that a boy could learn to be a lineman the same way he learned chemistry: by memorizing which elements and conditions led to a particular reaction.
Even now, the few people who do try to train vision often don’t bother to figure out which skills are crucial.
Because of this, Farrow spends a lot of time simply trying to determine what it is experts see that amateurs don’t. Among other things, he uses an eye-motion tracker to record where virtuoso players are looking during clutch situations, such as when passing under pressure from multiple defenders coming from different directions.
Farrow has created a video database of hundreds of critical decision-making moments, which he projects life-size onto a blank wall at the Crows training center. Players watch the simulations, which are from the point of view of the kicker, and “pass” the ball to the player they think is in the best position — literally kicking it at the wall.
Where players are getting better at reading serves, they are also also being taught how to hide their intentions. The result has been a kind of athletic arms race, the ability to read shots driving a corresponding need for better fakes.
These kind of dynamics can also be related to futurist society and technology predictions. Being able to analyze and determine earlier when certain events will occur and when the odds are shifting is a very useful advantage. A more regimented and scientific approach would be useful in determining how people can become better predictors. This means that predictions need to be tracked and analyzed.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.