New stats delivering Australian Open insights
This year’s Australian Open (AO) broadcast will look a little different, thanks to the inclusion of six new statistics that aim to offer additional insight into player performance.
The new data points have been developed by the Game Insight Group (GIG) — a partnership between Victoria University and Tennis Australia — and are part of a suite designed to deliver match predictions, strategy analysis and physical performance measurement.
Simon Rea is GIG Senior Manager of Game Analysis and said the new statistics focus on return of serve data, feats of defence and the use of the forehand from the back of the court.
“Epic tennis battles can be decided by the smallest of margins and our team aims to demonstrate exactly what has created those differences,” Rea said.
“The new stats complement the existing insights GIG has provided for the AO broadcast that predict who is going to win, impact of pressure points and the physical battle, all offering an opportunity for fans, commentators, players and coaches to truly see how spectacular some of the performances are.”
GIG comprises data scientists, computer engineers and sports scientists who have access-all-areas at the tournament to capture, analyse and visualise tracking data of both the ball and the player in addition to point outcome information during matches.
Victoria University Sports Analytics Professor Sam Robertson said the industry-leading insights showcase the university’s sports expertise on the world stage.
“The GIG team is revolutionising tennis through science and data analysis. In addition to helping fans to understand the game better, we also provide match play analysis to many of the world’s best tennis players and their coaches,” Robertson said.
“We are incredibly excited to be introducing the impactful six new insights into this year’s AO broadcast.”
For those with a keen interest in tennis — or statistics — the 2023 Australian Open GIG stats list is as follows, with new data points denoted by an asterisk:
- Win predictor — The win predictor considers data that experts don’t easily have access to. It provides an objective, data-driven view of what fans might come to expect in or before a match. The swing (in-match) predictor separates from the pre-match prediction increasingly as the match progresses, informed by the play on service games. It illustrates how remarkable some performances are via match fluctuations.
- Pressure points won — In close sets, pressure points identifies the winner of the set more accurately than more traditional stats. It’s best used when the player ahead on pressure points won is level/trailing on total points won but has the marginal advantage on the scoreboard, as this indicates superior performance on the points that matter most.
- Early breaks* — This is the percentage of times a player wins the set after breaking serve in one of the first four games of the set. It is calculated from performance on hard courts only over the past 12 months and emphasises the importance of the fast start.
- Break force* — Can a player land the break after creating multiple opportunities to do so? This measure speaks to the accumulation of pressure over time being placed on the server and is, again, calculated from performance on hard courts over the past 12 months.
- Break right back* — This stat highlights how frequently a break of serve is followed up immediately by another break — the “break right back”. For some of the very best returners in the game, being broken is not necessarily the hammer blow that it may be for others.
- Ultimate defender* — this shows the likelihood (in % terms), that a player pushed to the court extremities can survive in the point and go on to win out of the forehand and backhand corners. It shines a light on physicality and the ability to defend.
- On the rise %* — This illustrates the differences in approaches: either taking the ball on the rise or being forced/choosing to operate from deeper in the court as the ball descends off the bounce. It describes the % of balls being impacted on the rise and is based solely on the current match.
- Forehand heaviness — this provides a value to describe the combination of speed and spin a player generates on topspin forehand groundstrokes. It can be used to contrast the ball striking of two players or how one player’s weight of shot may change over the match.
- Hunting 3rd shot forehand %* — Looks solely at the 3rd shot of the point following first serves and measures the % of time that shot is taken as a forehand, as compared to a backhand. It offers opportunity to compare a FH versus BH approach and highlight the effectiveness of any mid-match changes.
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Physical battle — Measures sheer physicality in the game using metrics like total distance, sprints and high intensity changes of direction, which tell the story of lower body capacity to accelerate and track down balls. Hitting load looks at the cumulative, upper-body effort that players put into their shots.
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