Using Numbers to Redefine T20 Cricket
When it was launched in 2003, T20 cricket was considered no more than a more commercial format of the sport, which was a bit of fun, and provided a quick result for maximum entertainment.
It seemed like it was more entertainment, than sport. It was not cricket as we had known it to be.
The game's traditional format - Test Cricket - is far more meticulous with the better team almost always triumphing after five days of good competitive cricket. While, the middle format - ODIs - is somewhere in between.
The longer the format, the more exposed one's skill is and the likelihood of an upset is very low. Which is why T20 cricket provides for more intense and competitive games. It is the most random of the three formats of the game and in a shorter period of time any team can come out on top.
As the balance of power within cricket has swung towards T20, money and research has poured in to work out how to be successful in T20 cricket.
The T20 format has prompted a significant increase in the use of data analysis to improve recruitment, selection, and tactics, in a way that has never been used previously. Mumbai Indians, who are favorites to win the IPL as per the latest IPL betting, have used this to drive home huge success.
“There is a weird paradoxthere,” says Tim Wigmore, journalist for The Independent and co-author of Cricket 2.0, a book about the T20 revolution.
“T20 is the most random format
in that it takes the smallest number of deliveries to swing the course of a
match, but it can also be planned. It gives you a far better opportunity to use
data to plot your path to victory.”
The best managed T20 teams have
learned how to use data to gain an edge in all departments of the game.
Teams are able to access
averages, strike-rates, boundary percentages and much more in every phase of
the innings at the click of a button.
If a team requires a batsman
who hits at a strike-rate of 200 in the last five overs, for example, they can find out who has a track
record of doing so.
Data is also used far more
regularly to determine weaknesses in oppositions and to deploy tactics for
specific matches.
Technological improvements
have also coincided with the rise of T20 cricket, but that is not the only reason why
this format has been most influenced by data analysis.
“There is so much more data to
work with in T20 cricket,” says Wigmore. “The scenarios repeat themselves so
much more often.
“You have so many variables in
Test cricket. If you’re batting on a day-five pitch that is turning a certain
amount, you might only have come across that scenario once or twice a year
because of the number of things that need to take place in a Test match to get
there.
“T20 scenarios do repeat
themselves. You can plan for the 15th over when a certain batsman is well
set because it happens so often.
“There are so many more
top-level T20 matches. A top T20 player might play 50 matches per year, while a
top Test player might play 12 or 13. It actually gives you a proper sample size
to work with.”
The driving force behind the popularity of T20 cricket has been franchise leagues - the IPL, PSL, Big Bash, CPL - almost all nations have a league of their own. Salary caps and restrictions on number of overseas players allowed maintain the balance of the sides making the league more competitive.
Due to such restrictions, smart use of technology and data provide teams with a significant competitive edge.
The Mumbai Indians, who have won the IPL more times than any other team, have utilized data analysis the best among all T20 teams around the world.
“Mumbai Indians’ success has been rooted in out-thinking their opponents,” says Wigmore. “They are excellent at doing it before they even get to the auction able.
“They’ve got a very good idea
of how to assemble a team because they’ve used data to establish the best
strategy. Then they have a really strong scouting system that allows them to
chase all of the most undervalued domestic talent.
“It’s a bit of a myth that you
want to get the best overseas players – you actually want the players that add
the most value to the team, which is dependent on which local players are
available.
“For example, there is a
relative shortage of power-hitters at the death in India, so they’ve used an
overseas slot on Kieron Pollard, who’s a brilliant hitter.
“They’ve honed their
strategy.”
Teams that have nailed their
recruitment have placed themselves in the best position to master their tactical
approach, too.
‘Match-ups’ has become an increasingly popular buzz term around T20 cricket over the last few years. Teams use data to identify the weaknesses of individual opponents and work out how players within their squad can exploit them.
Exposing a rival’s weakness is
not new, but the use of numbers legitimizes the tactics.
“A lot of analysis for me is
about knowing what the bowlers have in their armoury,” says South Africa and
Rajasthan Royals batsman David Miller. “Their strengths and weaknesses.
“I want to know what they do
when they are under pressure. Whether they go to the yorker or the slower ball,
for example.
“Having that information
definitely helps swing the odds in your favour.”
Wigmore explains that there
are different ways that teams can use analysis of their opposition.
“You can plan it to a really
deep degree,” says Wigmore. “You can plan when you want to bowl specific
bowlers – I know Ricky Ponting says you can basically map out the entire
bowling innings – but another way is to plan which bowlers you want to bowl to
specific batsmen.
“For example, if your opening
bowler has a really good match-up against their number three batsman, you might
give them a third over with the new ball.
“A great example was the World
T20 final in 2016 when Joe Root opened the bowling against Chris Gayle. England
had worked out that Gayle against off-spin is not nearly as good as against
other types of bowling, and Root got him out.
“We saw in the South Africa v
England T20 series last year the England data analyst Nathan Leamon holding
signs up with codes that reminded Eoin Morgan of the various match-ups that had
been planned. That’s the degree to which players are working now.”
Morgan is a data enthusiast
who believes in that way of working, but studying the numbers does not work for
all players.
“I was never looking to take
down certain bowlers that suited me – I didn’t look at things in that way,”
says Kevin Pietersen, 2010 World T20 champion and one of the IPL’s greatest
overseas players.
“If I decided during the match
that a bowler had to go, then it didn’t matter who it was. It was game-based,
so I didn’t plan it with analysis beforehand.
“I knew what my areas were,
though. As my career went on I became more aware of which balls I could hit and
begun to train my brain to recognise them early.”
Wigmore has spoken to players
on both ends of the spectrum.
“There are players who have
really embraced it,” he says.
“Look at Morgan and Pollard
over the last few years – they have looked at their numbers, worked out how
they can improve and have begun to start their innings much quicker.
“Quite a few of the West
Indies team that won that final in 2016 look into numbers, too. Carlos
Brathwaite second-guessed that Ben Stokes would bowl the yorker length in that
last over because the long boundary was on the leg-side. That was a brilliant
example.
“But most players don’t spend
a long time looking at the numbers. They can talk to analysts about
improvements they can make without even knowing the numbers behind it.”
An apparent divide between
data sceptics, cast as stuffy and old-fashioned in their views, and data
enthusiasts, forward-thinking and progressive, has emerged among cricket
supporters over the last few years.
While there is no denying that
teams using a data-driven approach enjoy lots of success, Wigmore argues that
there is still a place for gut feel, instinct and an innate understanding of
the game.
“Data can’t measure
everything,” he says. “There will always be something that the model can’t
account for on the day.
“It maybe can’t account for
the wind or the dew or an injury, or whatever. I don’t think anybody is
actually trying to say that gut feel is being replaced. I don’t think that’s
how it’s being sold, and rightly so.
“But data can be used as a way
of challenging and improving your decision-making. It is a really useful tool
and increasingly important.”
While the analytics revolution gathers pace, you can be sure that those who are most open-minded to it will continue to flourish.
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