Duckworth-Lewis-Stern Method Explained: How Rain Affects Cricket Targets

Few moments in limited overs cricket cause as much confusion as a match interrupted by rain, followed by a broadcaster flashing a “revised target” on screen that seems to come from nowhere. Commentators talk about “resources.” Fans argue about whether the chasing team got a raw deal. Casual viewers often just trust the number without understanding where it came from. That number is not arbitrary though, and it is not a black box either. It comes from the Duckworth-Lewis-Stern method, usually shortened to DLS. It is one of the more elegant pieces of applied statistics in professional sport. This guide explains what it actually does, why it exists, how it replaced far cruder methods used in cricket’s earlier decades, and how to read a DLS affected scorecard without squinting at the numbers in confusion.

A Brief History of Rain Rules Before DLS

Cricket’s earliest attempts at handling rain shortened matches were blunt instruments by comparison. The most notorious was the “most productive overs” method used in the 1992 World Cup. It recalculated a revised target by simply removing the opposition’s least productive overs from their innings. That method became infamous for producing wildly unfair results. Its most cited failure came in a semi final. South Africa’s target went from a gettable 22 runs off 13 balls to an effectively impossible 22 runs off just 1 ball after a rain delay. That happened purely because of how the calculation handled the reduction. That single moment became the case study that pushed cricket toward a genuinely mathematical solution. It arrived a few years later in the form of Duckworth and Lewis’s original method.

The Problem DLS Was Built to Solve

Before any formal method existed, rain affected targets were often set using simple run rate math. If a chasing team’s overs were cut in half, their target was roughly cut in half too. The flaw becomes obvious once you think about it. A team with wickets in hand and overs to spare can accelerate very differently than a team that has already lost half its side while cautiously building an innings. Treating every over as equally valuable, regardless of how many wickets remain, kept producing targets that favored one side or the other depending on the specific match situation. Cricket needed a method that accounted for both variables at once. Overs and wickets together, not overs alone.

Where the Name Comes From

The method takes its name from three statisticians. Frank Duckworth and Tony Lewis developed the original formula in the 1990s. It was adopted by the ICC in 1999 after proving itself in domestic English cricket. In 2014, Professor Steven Stern refined the underlying model using a larger and more modern dataset of match results. The method was renamed Duckworth-Lewis-Stern in his honor. The core idea has not changed since the 1990s. Only the precision of the numbers behind it has improved.

How “Resources” Actually Work

The concept at the heart of DLS is resources. This is a single percentage figure showing how much scoring potential a team has left, combining both overs remaining and wickets in hand. A team with 30 overs left and all ten wickets standing has far more resources than a team with 30 overs left but only two wickets in hand, even though the overs number is identical. This is the key idea that separates DLS from naive run rate scaling. It never looks at overs on their own.

When a match is shortened, DLS compares the resources available to each team rather than the raw overs. If the team batting second has fewer resources than the team batting first had for their full innings, the target scales down. In rarer multi interruption scenarios, the second team can end up with more resources than the first team had. When that happens the target scales up instead, using the tournament’s average score as a reference point.

A Worked Example

Say Team A bats first and scores 250 in a full 50 overs, using all of their resources, 100 percent. Rain then delays the start of Team B’s innings, cutting their available overs down to 35, with all ten wickets still in hand. Team B’s resource percentage for 35 overs might come out to roughly 79 percent. Fewer overs, but no wickets lost yet. DLS would then set Team B’s target at approximately 250 times 79 over 100, which works out to around 198, plus one to win. Compare that to the naive proportional cut of 250 times 35 over 50, which would have demanded only 175. The difference reflects a simple fact. Team B still has full batting depth to attack those 35 overs aggressively, something a pure overs ratio calculation ignores entirely. Try your own scenario with the DLS Calculator. It also supports checking a live “par score” mid chase, not just the target before an innings starts.

Common Myths About DLS

A few misconceptions come up again and again around DLS, so it is worth addressing them directly. First, DLS is not designed to be exploitable. Teams cannot meaningfully game the resource table by batting a certain way. The model is based on historical scoring patterns across thousands of matches, not a simple formula that is easy to reverse engineer mid innings. Second, a lower target under DLS does not mean the chasing team was gifted an easier game. It reflects a genuinely smaller batting resource, which usually comes with genuinely less time to build an innings safely. Third, DLS applies to any playing time interruption, not just rain specifically. Bad light, an unplayable outfield, or any other approved stoppage triggers the same calculation. Fourth, DLS is not unique to international cricket. Every major domestic T20 league uses the same method for rain affected matches, so the target logic in an international final is identical to what decides a rain hit franchise league group match.

Where DLS Shows Up Most Often

Rain affected targets are a near yearly storyline in tournaments played during monsoon seasons or unsettled weather windows. The IPL has seen several DLS decided results during its rain prone April to May window. The PSL has had its own share of weather interrupted finishes in Pakistan’s early season fixtures too. Whenever you see a match status change mid innings with a revised number appearing on screen, that is DLS at work. Checking the Today’s Toss Winner page and the Today’s Match Schedule page is a quick way to see which matches are live and potentially weather affected right now.

The Bottom Line

DLS is not trying to guess what “would have happened” if the match had continued uninterrupted. No method could do that reliably, and DLS does not try to. Instead it solves a narrower and more honest problem. Given exactly how much batting resource each team actually had, what target keeps the contest as fair as mathematically possible? That framing is what separates DLS from every rain rule that came before it. It is not chasing a perfect prediction of an alternate reality. It is offering a defensible, consistent standard applied the same way in every rain affected match, everywhere in the world. Once you see it through that lens, DLS goes from a confusing broadcast graphic to one of the more genuinely well designed pieces of sports math in use today. For more cricket explainers like this one, browse the Cricket section on CricSport.