DLS Method Explained: How the Duckworth-Lewis-Stern System Works in Cricket

# DLS Method Explained: How the Duckworth-Lewis-Stern System Works in Cricket

Few things confuse cricket fans more than a rain-affected match. One moment your team is cruising to victory, the next the covers are on, and when play finally resumes, the commentators announce a revised target that seems to have come from nowhere — or the match is declared over with a winner decided by something called “DLS.” If you have ever stared at a “par score” graphic wondering what on earth it means, this DLS method explained guide is for you.

The Duckworth-Lewis-Stern method — usually shortened to DLS — is the mathematical system used in international and most professional limited-overs cricket to set fair targets when rain, bad light or other interruptions reduce the number of overs available. It replaced the older, widely criticised rain rules that produced some of the most unfair results in cricket history. Love it or hate it, DLS is central to modern limited-overs cricket, and understanding it will transform the way you watch rain-affected matches.

In this guide, we break down the DLS method explained in plain English: what “resources” and “par scores” actually mean, why the system was updated from Duckworth-Lewis to Duckworth-Lewis-Stern, a fully worked illustrative example, how DLS differs between ODIs and T20s, and why it still drives fans mad. No advanced mathematics required — just a willingness to think about cricket a little differently.

What Is the DLS Method?

The DLS method is a formula that answers a deceptively simple question: when a limited-overs match is interrupted and overs are lost, what is a fair revised target for the team batting second?

Before DLS (and its predecessor, Duckworth-Lewis), cricket used crude rain rules. The most notorious was the “average run rate” method, which simply compared the two teams’ run rates — a system that punished the team batting second for losing wickets sensibly and produced farcical results. The most infamous example came in a major tournament semi-final where a team needing 22 runs off 13 balls returned after rain to need 22 runs off 1 ball. Everyone agreed the system was broken.

The insight behind Duckworth-Lewis — developed by statisticians Frank Duckworth and Tony Lewis in the 1990s — was that a team’s ability to score runs depends on two resources combined: the overs remaining and the wickets in hand. A team with 10 overs left and all 10 wickets in hand has far more scoring potential than a team with 10 overs left and only 3 wickets in hand. Any fair rain rule must account for both.

The DLS method therefore calculates, at any point in an innings, what percentage of a team’s total scoring “resources” remain. When overs are lost to rain, the resources available to one or both teams are reduced, and the target is adjusted proportionally. The team that has lost the greater share of its resources gets a correspondingly adjusted target. It is elegant in concept, even if the implementation involves some serious mathematics.

From Duckworth-Lewis to Duckworth-Lewis-Stern: A Brief History

The Duckworth-Lewis method was first used in international cricket in 1997 and became the standard rain rule for ODIs and later T20 internationals. For nearly two decades, “D/L” was the abbreviation fans saw on scorecards. But as T20 cricket exploded and scoring patterns evolved, a flaw became apparent: the original Duckworth-Lewis tables were built on data from an earlier era of one-day cricket, and they did not fully reflect how modern teams score — particularly the way teams accelerate dramatically in the final overs of an innings.

In 2014, the system was updated by Professor Steven Stern of Queensland University of Technology, who recalibrated the underlying model using modern scoring data. The updated version was renamed the Duckworth-Lewis-Stern method, and “DLS” replaced “D/L” on scorecards from that point on. The ICC adopted it across international cricket, and it remains the standard today.

The Stern update matters because it changed outcomes in a meaningful way. Under the old tables, teams batting first in high-scoring modern matches were arguably under-rewarded when rain intervened; the recalibration recognised that teams now score a larger proportion of their runs late in the innings. For fans, the practical difference is that DLS targets in the T20 era tend to feel slightly more generous to the chasing team than the old D/L targets did — though “fair” remains a matter of fierce debate, as we will see.

The Core Concept: Resources, Not Runs

Here is the heart of the DLS method explained simply: DLS does not think in runs. It thinks in resources.

A team’s resources at the start of an uninterrupted innings are defined as 100%. Those resources are a combination of:

• Overs available — the more overs, the more scoring opportunity.
• Wickets in hand — the more wickets remaining, the more aggressively a team can bat.

As the innings progresses, resources are consumed: every over bowled and every wicket lost reduces the percentage remaining. The relationship is not linear — losing your 9th wicket costs you far more resources than losing your 1st, because a team with one wicket left cannot bat with any freedom at all.

The ICC publishes (and software implements) a resources table: a large grid where one axis is overs remaining and the other is wickets lost, and each cell gives the percentage of resources remaining. For example, a team starting a 50-over innings has 100% resources. After 25 overs with no wickets lost, roughly half the resources are gone — but not exactly half, because the wickets in hand mean the remaining overs are actually more valuable than the overs already faced. This non-linearity is the whole point.

When rain interrupts, the umpires and match officials calculate:

1. The resources available to Team 1 at the start of their innings (usually 100%, unless their innings was also interrupted).
2. The resources available to Team 2 at the start of their innings (reduced if overs were lost before or during their chase).
3. The difference — the resources lost — determines how much Team 2’s target is scaled down.

If Team 2 has fewer resources than Team 1 had, their target is reduced proportionally. If Team 2 somehow has more resources (rare, but possible in odd interruption patterns), the target can actually be increased — though playing conditions usually cap this.

What Is a Par Score?

The par score is the concept most fans encounter during a rain-affected chase, and it is beautifully simple once you grasp resources. The par score is the total that the chasing team needs to have reached at the moment of interruption to be considered level with the team that batted first.

Here is how it works: suppose Team 1 scored 280 in their 50 overs (using 100% of their resources). Rain then reduces Team 2’s innings to 40 overs, giving them, say, 89% of the resources Team 1 had. Team 2’s revised target becomes roughly 89% of 280, adjusted by the formula — let’s say 251.

Now suppose rain stops play during Team 2’s chase, after 25 overs, with Team 2 on 150 for 2. Are they ahead or behind? The officials calculate how many resources Team 2 have used by that point and compare it with the resources Team 1 used to reach an equivalent stage. The par score is the score Team 2 would need at that exact moment — with those wickets lost — to be exactly level. If Team 2’s actual score is above par, they are ahead; if below, they are behind.

This is why you see graphics during rain breaks saying “Par score: 172 — Team 2 are 8 runs ahead.” If no further play is possible and Team 2 are ahead of par, they win. If they are behind par, they lose. If scores are exactly level with par, the match is tied. It is worth noting that par score comparisons only decide the match if a minimum number of overs have been bowled in the second innings — 20 overs in an ODI, 5 overs in a T20I — which we will come back to.

DLS Method Explained Through a Worked Example (Illustrative — Not a Real Match)

The following is a simplified hypothetical example to illustrate the logic. Real DLS calculations use the full resources table and precise formulas applied by match officials and software — the numbers below are rounded for clarity.

The scenario: In a 50-over ODI, Team A bats first and scores 280 all out in 48 overs. Because they were bowled out, they used 100% of their resources (being all out always counts as 100% resource usage, even if overs remain).

Rain arrives during the innings break and delays the start of Team B’s chase. When play resumes, the umpires determine that Team B’s innings must be reduced to 40 overs.

Step 1 — Calculate Team B’s resources. Consulting the resources table: a team starting an innings with 40 overs available and 0 wickets lost has approximately 89% of the resources of a team starting with 50 overs. (The exact figure comes from the official table; 89% is a reasonable illustration.)

Step 2 — Calculate resources lost. Team A had 100%. Team B has 89%. Team B has lost 11% of the resources Team A enjoyed.

Step 3 — Adjust the target. Team B’s target is scaled to reflect their reduced resources. Using the standard DLS scaling for this situation, Team B’s revised target would be approximately 251 off 40 overs (the precise figure depends on the official calculation, which includes a small adjustment factor for the scoring patterns of the first innings).

Step 4 — The chase and a second interruption. Suppose Team B reaches 140 for 2 after 25 overs when rain returns and no further play is possible. Are they ahead or behind?

The officials now calculate the par score. Team B, at 25 overs into a 40-over innings with 2 wickets down, have 15 overs remaining with 8 wickets in hand. The resources remaining at that point are roughly 45%, meaning they have used about 44% of their 89% allocation. The par score — the score at which Team B would be exactly level with Team A’s achievement — works out to approximately 134.

Team B are on 140, which is 6 runs ahead of par. Result: Team B win by 6 runs (DLS method).

Notice what happened: Team B were scoring at 5.6 runs per over, well below the 6.27 they needed for the revised target — yet they win, because they had wickets in hand and the par score accounts for the acceleration they would have been expected to produce in the remaining overs. This is exactly the kind of result that feels wrong to casual fans but is mathematically consistent within the DLS framework: wickets in hand are a genuine resource, and DLS credits the batting team for preserving them.

The DLS Formula in Plain English

For those who like to see the machinery, the standard DLS calculation for a reduced second innings works like this:

• Let R1 = resources available to Team 1 (usually 100%).
• Let R2 = resources available to Team 2 (less than 100% if overs were lost).
• Let S = Team 1’s score.

If R2 is less than R1, Team 2’s target T = S × (R2 / R1), rounded up, plus one run to win. (In practice, the ICC’s implementation includes a modest adjustment — the “G50” factor, representing the average 50-over score — which fine-tunes targets in very high- or low-scoring games. The full professional calculation is done by software, not by hand.)

When the first innings itself is interrupted, the calculation is done in stages: Team 1’s innings is divided into segments, the resources available in each segment are summed, and the total gives R1. Interruptions during the second innings are handled similarly, recalculating R2 from the point of interruption.

You do not need to memorise any of this to enjoy cricket. The takeaway is that every DLS decision flows from one principle: compare the resources each team actually had, and scale the target accordingly. Everything else is arithmetic.

DLS in ODIs vs T20s: Key Differences

The DLS method applies to both ODIs and T20 internationals, but the shorter format creates some important differences:

Minimum overs for a result. In an ODI, at least 20 overs must have been bowled in the second innings for DLS to decide a match; in a T20I, the minimum is 5 overs. If rain ends the match before these thresholds, the game is a “no result” (or abandoned), regardless of who was ahead. This is why a T20 can produce a DLS result after just a few overs of the chase — sometimes controversially.

Volatility. T20 cricket is inherently more volatile than ODI cricket — a single over can swing a match dramatically. DLS, which is built on average scoring patterns, can feel particularly brutal in T20s. A team that loses two quick wickets just before rain in a T20 chase will find the par score punishing, because the model assumes they would have struggled to accelerate. Conversely, a team with wickets in hand gets generous credit for acceleration that, in a real T20, might never have materialised. This volatility is a big part of why DLS generates more arguments in T20 cricket.

Strategic awareness. In rain-threatened T20s, professional teams now bat with DLS explicitly in mind — keeping wickets in hand and staying ahead of the par score becomes a tactical objective in itself. Captains and analysts track the par score ball by ball when dark clouds gather. In ODIs, with more overs to absorb interruptions, DLS tactics are less dominant but still significant in the final 15 overs of a chase.

If you want to see how modern ODI batting has evolved — the kind of aggressive scoring that forced the Stern recalibration — our rundown of the fastest ODI centuries of all time shows just how dramatically run-scoring has accelerated in the white-ball era.

When DLS Can’t Save a Match

DLS is powerful, but it has limits. If the interruption is so severe that the minimum overs cannot be completed — fewer than 20 overs in the second innings of an ODI, or fewer than 5 in a T20I — there is no result, and in a tournament this usually means the points are shared. This can feel deeply unsatisfying when one team was clearly dominant, but the thresholds exist for a reason: below them, the sample of play is simply too small for any statistical model to produce a meaningful result.

DLS also cannot be applied if the first innings never started — you cannot set a revised target without a first-innings score to scale from. And in multi-day cricket (Tests and first-class matches), DLS is not used at all; those formats have their own mechanisms (declarations, follow-ons, and simply the passage of time) for dealing with lost play.

Tournament playing conditions sometimes add their own wrinkles, such as reserve days for knockout matches or adjusted minimum-over thresholds. The ICC publishes the official playing conditions for each tournament, and they are worth a look if you want to understand exactly how DLS will be applied in a specific event like the Cricket World Cup 2027.

Why Fans Love to Hate DLS

For all its mathematical elegance, DLS remains one of cricket’s most argued-about institutions. The complaints fall into a few familiar categories:

It feels unfair in the moment. The worked example above shows why: a team can be behind the required run rate yet win, or ahead of it yet lose, because wickets in hand count as heavily as they do. To a fan watching the scoreboard, this looks like the maths overriding the cricket. Defenders of DLS reply that this is precisely the point — the scoreboard run rate was never the right measure, because it ignores the value of preserved wickets.

It is opaque. The resources table and the G50 adjustment are not intuitive, and for years the ICC did not publish the full table publicly. Fans are asked to trust a calculation they cannot reproduce. (The tables are now more accessible than they once were, and several apps and websites offer DLS calculators, but the perception of a “black box” persists.)

It struggles with T20 volatility, as discussed above. The model’s averages smooth out exactly the kind of explosive passages that define T20 cricket, and when a match turns on one over, DLS can look clumsy.

Famous controversies linger in the memory. Every fan of a certain age remembers matches where DLS (or its D/L predecessor) produced a result that felt unjust — a team punished for sensible cricket, a chase rendered impossible by a few lost overs. These memories calcify into distrust, even as the system itself has improved.

That is the honest verdict of this DLS method explained guide: it is the best system anyone has devised, not a perfect one. Every alternative proposed over the years — and there have been many — has failed to handle the two-resource problem (overs plus wickets) as coherently. Cricket’s lawmakers continue to review it, and the Stern recalibration shows the system can evolve. But as long as rain interrupts cricket, somebody will feel hard done by, and DLS will take the blame.

Practical Tips: Understanding DLS as a Viewer

You do not need to calculate DLS yourself, but internalising the key ideas from this DLS method explained guide will make rain-affected matches far more enjoyable to follow. A few habits help:

• Watch the par score, not just the required run rate. Broadcasters now show the par score routinely during rain-affected chases. If your team is above par with wickets in hand, they are in good shape even if the required rate looks steep.
• Wickets are worth more than you think. In a rain-threatened chase, a team that is 120 for 1 is in a dramatically better DLS position than a team that is 120 for 4, even though the scoreboard looks similar. Commentators will flag this — now you will know why.
• Know the minimum-overs thresholds. 20 overs in an ODI, 5 in a T20I. If rain is falling and the chasing team has not reached the threshold, the players may be desperate to get back on — every ball matters enormously.
• Follow the analysts. When dark clouds gather in a big ODI series — like the recent India vs Australia ODI series — the broadcast’s data analysts will talk DLS scenarios explicitly. Listening to them is the fastest way to build intuition.
• Use a DLS calculator app. Several free apps let you input the match situation and see the par score and revised target. Playing with one during a rain break is genuinely fun and builds understanding fast.
• Check ESPNcricinfo’s ball-by-ball. ESPNcricinfo‘s live coverage includes DLS par scores during affected matches, alongside excellent explanations from their commentators when things get complicated.

FAQs About the DLS Method

1. What does DLS stand for in cricket? DLS stands for Duckworth-Lewis-Stern, named after statisticians Frank Duckworth and Tony Lewis, who created the original method, and Professor Steven Stern, who recalibrated it in 2014. It is the official system used to calculate revised targets in rain-affected limited-overs matches.

2. How is the DLS target calculated? In simple terms, DLS compares the scoring “resources” (overs remaining combined with wickets in hand) available to each team. If the chasing team has fewer resources than the team that batted first — because overs were lost to rain — their target is scaled down proportionally using the official resources table. The full calculation is performed by match officials using ICC-approved software.

3. What is a par score in DLS? The par score is the score the chasing team needs to have reached at the moment play is interrupted to be considered exactly level with the first-innings team. If the chasing team’s score is above par when no further play is possible, they win; if below par, they lose; if exactly level, the match is tied.

4. What is the difference between Duckworth-Lewis and Duckworth-Lewis-Stern? Duckworth-Lewis was the original system, used from 1997. In 2014, Steven Stern updated the underlying statistical model to reflect modern scoring patterns — particularly the faster scoring in the final overs of modern limited-overs innings. The updated version was renamed Duckworth-Lewis-Stern (DLS). The core logic is the same; the numbers were recalibrated.

5. How many overs are needed for a DLS result? In an ODI, at least 20 overs of the second innings must have been completed for DLS to decide the match. In a T20 international, the minimum is 5 overs. If rain prevents these minimums from being reached, the match is a no result (points shared in tournaments).

6. Can the target ever increase under DLS? Yes, though it is rare. If the chasing team ends up with more resources than the first-innings team had — which can happen with unusual patterns of interruptions — the target can be adjusted upward. Tournament playing conditions sometimes cap such increases, so the exact treatment depends on the competition’s rules.

7. Why does DLS seem to favour the team with wickets in hand? Because wickets are a genuine scoring resource. A team with 8 wickets in hand and 10 overs left can score far more aggressively than a team with 3 wickets in hand and the same overs remaining. DLS quantifies this using historical scoring data. It can feel counterintuitive when a team behind the run rate wins, but the system is crediting them for resources (wickets) they preserved.

8. Is DLS used in Test cricket? No. DLS is only for limited-overs cricket (ODIs and T20s). Test matches and other multi-day cricket deal with lost time differently — through declarations, follow-ons, and the fact that teams can simply bat on when play resumes. There is no target to revise in an unfinished Test innings in the same way.

Key Takeaways

• DLS measures resources, not runs: a team’s scoring potential = overs remaining × wickets in hand, and rain reduces those resources.
• The par score is the level-score benchmark during an interrupted chase — above it you are winning, below it you are losing.
• Duckworth-Lewis became Duckworth-Lewis-Stern in 2014, when Steven Stern recalibrated the model for modern, faster scoring.
• Minimum overs for a result: 20 in ODIs, 5 in T20Is — below that, it is a no result.
• Wickets in hand matter enormously under DLS, which is why teams protect wickets when rain threatens.
• It is the best available system, not a perfect one — T20 volatility and the “black box” perception keep the debates alive.

Conclusion

The DLS method explained in one sentence: when rain steals overs, DLS steals a fair share of the target to match, by measuring what each team truly had to work with — overs and wickets together, not just the scoreboard.

It will never be loved. No formula can capture the romance of a chase, the momentum of a batting side in full flow, or the gut feeling that your team was “winning” when the heavens opened. But before Duckworth and Lewis, rain rules produced results so absurd they brought the game into disrepute. DLS replaced farce with fairness — imperfect, occasionally baffling fairness, but fairness grounded in real data about how cricket is actually played.

The next time the covers come on and the par score graphic appears, you will know what you are looking at: not a random number, but a careful estimate of where the game truly stands. And in a sport as weather-dependent as cricket, that understanding turns one of the game’s most frustrating moments into one of its most fascinating. Keep an eye on those wickets in hand — under DLS, they are worth their weight in runs.