The Duckworth-Lewis-Stern technique (DLS) is a mathematical formula used to compute the target score (number of runs needed to win) for the team batting second in a limited-overs cricket match that is postponed due to bad weather or other circumstances.
The Duckworth-Lewis-Stern technique (DLS) is a mathematical formula used to compute the target score (number of runs needed to win) for the team batting second in a limited-overs cricket match that is postponed due to bad weather or other circumstances. Frank Duckworth and Tony Lewis, two English statisticians, created the Duckworth-Lewis technique (D/L) (not to be confused with former cricketer Tony Lewis).
The ICC formally adopted it in 1999 after it was initially presented in 1997. After they retired, Professor Steven Stern replaced Duckworth and Lewis as the system’s curator. The method’s current name was given to it in November 2014. The ideal score in unbroken cricket matches is one run more than the total number of runs scored by the team that batted first. When overs are lost, it can be more difficult to set an adjusted goal for the team batting second than to reduce the run target in proportion to the number of overs lost.
This is because, for instance, a team with ten wickets in hand and 25 overs to bat might play more aggressively than if they had ten wickets and 50 overs to bat, which increases their run rate. The DLS method tries to find a statistically reasonable target with a similar difficulty level to the initial aim for the second team’s innings. Each team in a limited-overs match has two resources: the number of remaining overs and the number of wickets they can use to score runs. When the two resources are changed concurrently, the objective is changed proportionally.
How is the Duckworth-Lewis-Stern Method used?
The DLS Method is based on the straightforward equation shown below:
The par score is the number of runs needed by the team batting second to tie the game. For instance, rain forced the game to be halted after Rising Pune Supergiants’ 18th over in an IPL 2016 encounter against the Kolkata Knight Riders, restricting the Kolkata Knight Riders’ innings to just 9 overs. As a result, their goal was reduced to 66. This slightly exceeds the goal of 61, which would have been accomplished with the “Standard Edition.”
The efficacy of the Duckworth-Lewis-Stern method
The distribution of games won by teams who bat first and those who field first is reasonably even, according to the dataset of more than 6000 Twenty-20 games played between 2003 and 2017. This holds true even for games that used the DLS system after being canceled due to weather. When we count the games played in the Indian Premier League between 2008 and 2018, the divide is significantly different.
The side fielding first won 74% of the games where the DLS approach was applied, which is worrying. This is in contrast to the games played under normal circumstances, where teams that batted first or second took home the prizes fairly evenly. Even though this analysis is based on a tiny sample size of only 19 games, the fact that this split exists does point to a structural issue with the DLS technique, which needs to account for the explosiveness and fast-shifting nature of a T20 game.
The original Duckworth-Lewis Method‘s average score in a 50-over game was 245 points. This run rate has an intermediate run score per over of 4.90. In the first innings of Indian Premier League matches, an average of 162.11 runs are scored, which equals an 8.11 run rate. This is significantly higher than the norm when Duckworth and Lewis devised their methodology. This gives some support to the idea that a T20 match’s remaining overs are a resource that is far more valuable than its 50-over counterpart. The boxplot that follows shows how quickly T20 game scores can increase.
So what are the options?
The DLS Method outperforms its predecessors. However, this only makes up for some of its shortcomings. Given the data being gathered, developing a system that incorporates batters’ strike rates, bowlers’ economy, and averages is becoming increasingly feasible. At least at the game’s highest level, using the plethora of statistical tools and the availability of player- and match data makes sense.
The stakes are so high that it is worth a chance, even though the system would become even less transparent and more difficult to understand. It is hard to account for every scenario because the result of a cricket match could alter in the span of a few deliveries. But the existing system can still be improved. All you can do while a renovation is needed is watch your favorite team’s upcoming game and hope the rain gods are on your side.
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