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Garbisi Lines Up A Kick
Audience Engagement, Media & Technology

How Our New Kick Predictor Is Enhancing Rugby Storytelling

 

There is no getting away from it, kicking is one of the most important factors in rugby. In fact, since 1999, nearly one in five matches involving international teams who compete in either the Rugby Championship or Six Nations have been decided by three points or fewer. Stats Perform’s new Kick Predictor model, powered by Qwinn, is revolutionising the way we think about putting boot to ball.

By: Ben Jermy
Garbisi Lines Up A Kick

We have all heard of Expected Goals (xG) in football. First introduced in 2012, it has become a staple metric among broadcasters, analysts, and fans alike. The Kick Predictor is rugby’s answer to xG and was heavily utilised during the 2022 Guinness Six Nations.

Kick Predictor In Use

Stats Perform’s Kick Predictor model applies historical Opta kicking data, coupled with powerful Qwinn AI modelling, to calculate the likelihood of a kicker scoring from their attempt at goal. The model considers several factors, including a kicker’s previous rate of success, the difficulty of each kick based on field location and several venue-related adjustments. Unlike other similar models, Kick Predictor outputs are unique to each kicker and based on their individual historical kicking performance.

These insights are enabling broadcasters to deliver another layer of insight to rugby audiences, providing an engaging predictive element to live in-game action.

Through applying Kick Predictor, producers and editorial teams can generate:

  • Ratings for all international goal kickers
  • An Expected Success Rate, based on the difficulty of their kicks
  • Establish the proportion of ‘difficult’ kicks attempted
  • Compare a player’s actual success rate to their expected projection

How Kick Predictor is enriching pre-game analysis

Let’s look back to the first weekend in this years’ Six Nations. Scotland vs England in a sold-out Murrayfield, two of the most exciting fly halves in world rugby in Marcus Smith and Finn Russell. But who is the better kicker?

Russell vs Smith

The BBC utilised Kick Predictor pre-game to tell the story of the fly-halves, with Gabby Logan remarking that “Smith kicks more than you’d think and actually Russell kicks less than you think”.

The BBC were able to showcase this compelling story between two kickers thanks to our Opta Help Desk Service.

Being able to identify key trends and talking points in the lead up to a game is more important than ever – utilising new predictive data outputs can empower storytellers to cut through the noise giving viewers a fresh and interesting perspective backed by historical Opta data.

How can Kick Predictor help enhance a viewer’s in-game experience?

It’s very easy to overlook the importance of a team making their kicks, tries often being the preferred currency from a fan’s perspective. The importance of kicking is usually only realised in the dying moments when a team has a kick to win or as often happens, a kick to lose.

Sale Sharks vs Bath in round 21 of the 2021-22 Premiership Rugby season is a great example of missed kicks costing the win. Rob Du Preez was having an uncharacteristically off game from the tee, missing an 83% Kick Predictor rated attempt, a 72% and a 69% chance, amounting to nine very important points, especially when you find yourself 14 behind at half time. Faf De Klerk took over kicking duties and slotted a tough conversion in the 66th minute, (rated at 59% using the Kick Predictor) giving the Sharks the lead for the first time since the early stages of the game. In the 83rd minute, De Klerk had a kick to win the game with a predicted success rate of 65%. He missed, and as a result faced the spotlight despite several easier kicks missed by Du Preez earlier in the match.

If we look at the historical kick prediction metric, we can see that compared to De Klerk’s kick likelihood the historical prediction had a rating of 71%, a much higher success rate, so should Du Preez have stepped up as the team’s primary (and historically successful) kicker? Would he have had a better chance of slotting the kick to win the game?

Kick Predictor, if applied to this fixture in a live setting, would provide fans with greater perspective to the relative difficulty of the kicks attempted in the game and add a new level of insight and importance to each kick as they happen, allowing broadcasters to ramp up the drama in the key moments when a game is won or lost.

Faf De Klerk Kicks From The Tee

How Kick Predictor can help tell the story of a game after the final whistle has blown

The Six Nations’ final weekend clash between Italy and Wales was a truly breathless affair, the Azzurri ending their 36-game winless streak in the competition with a 78th minute try. Ange Capuozzo beat three defenders and ran 53 metres before passing to Edoardo Padovani who ran it under the post, leaving 21-year-old Paolo Garbisi with an “easy” conversion to win the match…

But what if Ange hadn’t passed? As illustrated in The Analyst’s Six Nations Roundup, Garbisi’s eventual match winning conversion had an expected success rate of 97% according to Kick Predictor, bread and butter for a kicker the quality of Garbisi, but if Capuozzo had backed his own ability and scored in the corner the resulting kick would have had an expected kick success rate of just 47%. Before Kick Predictor we would never be able to truly understand how crucial that selfless pass was. Kick Predictor gives us the ability to enrich viewers in game experiences and appreciate crucial contributions and game clinching moments.

But would Garbisi have made the kick? Using our historical Opta data we can look at the difference between a player’s success rate and their expected rate and see if they are over/under performing off the tee. Garbisi ranks in the top 4 since 2018, slotting 79% of his kicks with a difficulty rating of over 72%.

Six Nations kicking stats since 2018

With matches so close, kicking is everything, fans on the edge of their seats every time a player opts for the tee. Our data allows fans an extra level of insight before every kick, bringing them closer than ever to the game they love.

How Kick Predictor could help elevate your 2023 Rugby World Cup post-match coverage.

Let’s hark back to one of the semi-finals of the 2019 Rugby World Cup. Wales took on the Springboks in a contest that could be described as “one for the purists”, with only one try a piece, and on average a kick out of hand every minute (81), it might not be considered a thriller. However, on further inspection and analysis this game was in fact a record breaker!

All nine kicks at goal during the match were successfully converted, with a Kick Predictor value of 58%. No other game in Rugby World Cup History has seen a 100% success rate with as difficult kicks, this game was a kicking masterclass. Handre Pollard’s 5/5 was especially impressive considering the difficulty of 4 of the positions. Our Kick Predictor has been applied to every RWC match going back to 1987, allowing us to generate these compelling insights and provide deep historical context.

Without the Kick Predictor delivering a fresh perspective, and the rich vein of historical data available with Opta, fans might have never appreciated what was a truly unrivalled display of kicking prowess.

Showcasing the deeper story behind the game is what really brings fans closer to the sports they love. These insights can be used by publishers and broadcasters on social media to initiate debates and discussions around the key moments in a game, driving engagement and signpost followers to match reports or feature articles.

Want to learn more about our Kick Predictor product and how it can transform your storytelling? Get in contact today.