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Abby Dow magic seals Red Roses' ticket to World Cup finals

Abby Dow runs in the match-defining try for the Red Roses. Photo by Andy Jackson - World Rugby/World Rugby via Getty Images

Seven months after breaking her leg, England’s Abby Dow has scored a length-of-the-field try to help her side to a Rugby World Cup semi-final win over Canada.

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England have booked their place in the women’s Rugby World Cup final with a nailbiting 26-19 win over Canada at Auckland’s Eden Park.

Abby Dow’s breathtaking length-of-the-field breakaway try 10 minutes into the second half was decisive.

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Less than seven months after breaking her right leg playing for England against Wales, Dow capped a move that started behind her own try line to break Canada’s resistance and send the tournament favourites to a record-extending 30th consecutive win.

With England 18-12 to the good, the Canadians had been camped on their opponent’s line, with several players going close to nabbing a crucial score.

After mounting pressure, England forced a turnover and set in motion a flowing move that ended with Dow racing from near halfway to touch down a memorable matchwinner.

“It was incredible,” England captain Sarah Hunter said.

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“Canada really tested us, for rugby fans I hope that was an advertisement for what women’s rugby is all about.

“Canada were relentless and the girls put their bodies on the line.”

Hosts New Zealand take on France later on Saturday as they look to retain the title they won in Ireland in 2017.

England, who last won the title in 2014 when they defeated the Canadians in France, will be appearing in the final for the sixth tournament in a row and eighth time in total.

“I am proud of the girls,” Canada head coach Kevin Rouet said of his side, who now look forward to the third-place play-off.

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“It’s about details and England were better than us on details.

“There are more than a few missed opportunities for us. We’ll be back.”

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J
JW 2 hours 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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