Tennis fans will be treated to new data analyses as part of the tournament’s official broadcast this year.
Some of these statistics might be familiar from other sports, but some are particularly unique to tennis.
The Game Insight Group (GIG) – a joint venture between Victoria University and Tennis Australia – has developed 10 new statistics that will provide a finer level of in-match detail to viewers at home and coaches on the court.
Working with data obtained from Hawk-Eye, which is responsible for the analysis of the green ball’s movement during matches, the GIG’s team of engineers, developers, analysts and data scientists convert this information into visualisations that can be used by broadcasters, and dashboards that can be viewed by the player’s box during matches.
Olivia Cant is a postdoctoral researcher from Victoria University who will help bring data to life at the Australian Open. Her job will be to quality-control the data coming to the GIG analysts from Hawk-Eye, and compile information and taking points that broadcasters can use to contextualise the contest.
Some of that data may prove a pivotal predictor of the outcome of the match.
“The player who wins more points doesn’t necessarily win the match,” Cant says. “That’s because of the tennis scoring system.”
“Not every point carries the same value: if you win the first point of a game, maybe that’s not quite as important as winning the last point. So we’ve come up with a stat with pressure points, and that looks at how many pressure points each player wins.
“For tight matches, that’s a better predictor of who wins, than just looking at the total points won.”
Pressure points will indicate the number of break points and tiebreaks won. GIG says four out of five matches are won by the player who claims more pressure points.
At the same time, GIG will be measuring physical parameters: and not just biological metrics either.
While the athletic outputs of the game will be tracked, the analytical technology will also measure the force behind the ball strike and converting this into useable information for broadcasters, commentators, and coaches in-court.
And because coaches will have access to this data, they can feed tips back to the athlete to tactically alter their game to neutralise their opponent.
This accessibility is what Cant believes will be the big upside for home viewers and the player’s team at this year’s open.
“Data has always been available for players to access if they request it, but they really needed an analyst to interpret it,” Cant says.
“If we sent a whole bunch of numbers, that probably wouldn’t make much sense.
“You really need somebody on your team that can interpret that, so I think it’s cool that we’re making it more accessible to players, to make that data live.”
The Australian Open runs from January 8-29.
The new metrics on your telly
Pressure points won: Indicates the number of break points, points that lead to a break point, and a tie break points won. In close sets, the number of pressure points is a better indicator of the likelihood that an athlete will win a set.
Early Breaks Converted: A percentage indicating how often a player wins a set after breaking serve in one of the first four games of a set.
Break Force: A measure of break points won divided by break point opportunities. Players with higher break force win 81% of matches.
Break Right Back: After being broken, does the player break back in the following game?
Ultimate defender: Measures how often a player pushed to the ‘extremities of the court’ survives and wins the point.
On the rise: Will measure the percentage of balls being hit on the post-bounce rise after the third shot opposed to on the fall, the latter suggesting deeper court position.
Forehand heaviness: This will add a value to describe the speed and spin on the ball generated by forehand ground strokes.
Hunting third-shot forehand: Will measure the times the server forehands their first post-serve hit, indicating their desire to dictate the point.
Physical battle: Will measure metres covered on the court, high intensity directional changes, hitting load (as a measure of how many shots are hit at 100 km/h or more and energy expended by the athlete.