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Watch: Burton and Gagai bringing back the biff in Origin III

(Source/Channel 9)

Burton and Gagai ignited an Origin series which had seemed timid and amicable until the 42nd minute at Suncorp Stadium on Wednesday when the centre duo traded fists.

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Gagai took exception to a shove on Maroons fullback Kalyn Ponga and went toe to toe with Burton to get the rowdy Queensland crowd up on their feet.

Both players were sin-binned by referee Ashley Klein at the time, but crucially won’t miss any club football after the NRL’s match review committee handed them monetary sanctions for grade two striking charges.

NSW centre Matt Burton and Queensland counterpart Dane Gagai have both escaped suspension after they brought the biff back to State of Origin in a compelling decider.

Burton and Gagai have been given a fine worth 23 per cent of their match fee with early guilty pleas and should both be available for Canterbury and Newcastle respectively.

Gagai was relieved when he learned of the news that he wouldn’t miss any club games while a crestfallen Burton struggled to comprehend the loss as he sported a big black eye.

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The Canterbury centre was inconsolable after the 22-12 defeat and insisted he had not sustained a fracture to his cheek or eyesocket.

“Whatever happens on the field stays on the field,” Burton said.

“You don’t want to get sent off and it obviously affects the team.

“The ref controlled the game and that’s up to his decision and that’s footy.

“I’m not the ref, he makes the decisions and that’s his call. It was obviously disappointing to not get the result.”

The only other player charged from the game was Queensland prop Tino Fa’asuamaleaui who hit Burton with a high shot in the ninth minute and was also involved in the fracas with Gagai, holding Burton back as Gagai laid into him.

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He faces a 20 per cent reduction in his match fee if he pleads guilty and will be cleared to play for Gold Coast against Brisbane on Saturday.

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J
JW 1 hour ago
Why Les Kiss and Stuart Lancaster can lead Australia to glory

It is now 22 years since Michael Lewis published his groundbreaking treatise on winning against the odds

I’ve never bothered looking at it, though I have seen a move with Clint as a scout/producer. I’ve always just figured it was basic stuff for the age of statistics, is that right?

Following the Moneyball credo, the tailor has to cut his cloth to the material available

This is actually a great example of what I’m thinking of. This concept has abosolutely nothing to do with Moneyball, it is simple being able to realise how skillsets tie together and which ones are really revelant.


It sounds to me now like “moneyball” was just a necessity, it was like scienctest needing to come up with some random experiment to make all the other world scholars believe that Earth was round. The American sporting scene is very unique, I can totally imagine one of it’s problems is rich old owners not wanting to move with the times and understand how the game has changed. Some sort of mesiah was needed to convert the faithful.


While I’m at this point in the article I have to say, now the NRL is a sport were one would stand up and pay attention to the moneyball phenom. Like baseball, it’s a sport of hundreds of identical repetitions, and very easy to data point out.

the tailor has to cut his cloth to the material available and look to get ahead of an unfair game in the areas it has always been strong: predictive intelligence and rugby ‘smarts’

Actually while I’m still here, Opta Expected Points analysis is the one new tool I have found interesting in the age of data. Seen how the random plays out as either likely, or unlikely, in the data’s (and algorithms) has actually married very closely to how I saw a lot of contests pan out.


Engaging return article Nick. I wonder, how much of money ball is about strategy as apposed to picks, those young fella’s got ahead originally because they were picking players that played their way right? Often all you here about is in regards to players, quick phase ruck ball, one out or straight up, would be were I’d imagine the best gains are going to be for a data driven leap using an AI model of how to structure your phases. Then moving to tactically for each opposition.

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