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• Harmanpreet Kaur replaced as India captain – but will she keep playing?
• Should ECB help fund a women’s Test in the West Indies?
• Big Bash privatisation – what is really being sold?

Batting

Bowling

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• WPL retentions – any surprises?
• Eva Gray signs for Hants – but where does that leave Essex?
• Vitality ditch the Blast
• The Afghanistan Premier League Shame List

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• Middlesex win the League 2 One Day Cup
• 2026 season review: your questions answered
• Who has earned a spot in the Wisden Five?
• England U19s squad announced
• Worrying news from the West Indies

Phase-adjusting three seasons of WBBL batting shows how raw strike-rate rankings systematically mark down openers.

By Zalak Kansara

Tammy Beaumont’s recent WBBL strike rate looks ordinary if it is read as a single number. Across the 2023-24 to 2025-26 competitions she scored 530 runs from 439 balls, a strike rate of 120.7. Among the 50 batters who faced at least 200 deliveries, that placed her 25th.

But those batters did not face the same mix of overs.

The WBBL contains four meaningfully different scoring phases. In this three-season sample, batters scored at 105.2 in the mandatory Powerplay, 112.7 in ordinary middle overs, 139.1 in non-Surge death overs and 155.5 during the Power Surge. The Surge was the highest-scoring phase, yet it accounted for only 9.6% of balls faced.

That matters because access to those phases is uneven. Openers faced only 4.9% of their deliveries during the Surge. The corresponding figure was 10.2% for batters whose median position was three or four, and 13.4% for middle and lower-order batters.

Raw strike rate therefore mixes two things: how quickly a batter scored, and the scoring environments in which she happened to bat.

A phase-adjusted comparison

To separate those effects, each batter’s expected runs were calculated from her own distribution of deliveries across the four phases and the competition strike rate in each phase. Actual runs were then compared with those expected runs and rescaled to the competition’s overall strike rate of 119.8.

The calculation is:

Expected runs = sum of balls faced in each phase multiplied by that phase’s league strike rate, divided by 100

Phase-adjusted strike rate = actual runs divided by expected runs, multiplied by the overall league strike rate

This is not an attempt to produce a definitive measure of batting quality. It asks a narrower question: how would the ranking look if each player’s output were judged relative to the scoring rate of the phases she actually faced?

The answer changes the shape of the table. The 17 openers in the 200-ball sample rise by an average of 6.1 ranking places after adjustment. The other 33 batters fall by an average of 3.1 places.

The shift is not driven by one player. Katie Mack rises 15 places, Beaumont and Chamari Athapaththu each rise 14, and Sophia Dunkley rises 11. Individual movements should not be treated as verdicts, but the group pattern is difficult to dismiss as a Beaumont-only effect.

Beaumont as an illustration

Beaumont faced 253 balls in the mandatory Powerplay, 172 in ordinary middle overs, 14 in the Surge and none in non-Surge death overs. Applying the full-precision league phase rates to that distribution produces 481.75 expected runs.

Her adjusted calculation is therefore:

530 actual runs divided by 481.75 expected runs, multiplied by the 119.76 league strike rate, produces 131.76, reported as 131.8.

That moves her from 25th by raw strike rate to 11th by the phase-adjusted measure, a rise of 14 places.

The adjustment does not say that 131.8 is her “true” strike rate. Nor does it claim that Powerplay batting is harder in every match. It says that Beaumont scored materially more runs than the league phase rates would predict from the particular mix of overs she faced.

Her zero death-over deliveries make her an unusually clear example. The wider result, however, is that openers as a group are less exposed to the fastest-scoring phase in the competition.

Does the result survive different choices?

The direction remains the same under four alternative specifications.

At a 300-ball eligibility threshold, openers rise by 4.6 places on average and everyone else falls by 2.9. When phase benchmarks are calculated separately for each season, openers rise by 5.9 and everyone else falls by 3.1. When the Surge is folded back into the underlying middle or death phase, openers still rise by 4.9 and everyone else falls by 2.5.

There is also a potential issue with rain-affected matches, because a fixed death-over definition is less natural in a shortened innings. Excluding all 17 matches in the sample that carried a D/L result or a reduced target leaves 47 eligible batters. Openers still rise by 5.3 places on average, while everyone else falls by 3.0.

None of those tests reverses the finding.

What this does and does not show

Phase adjustment deals with one source of context, not all of them. It does not control for match situation, opposition quality, ground dimensions, wickets in hand or the tactical role assigned to a batter. The phase rates describe what happened across the competition; they are not proof that one phase is intrinsically easier or harder.

The role labels are analytical rather than official. A batter is classified from her median batting position across her innings in the sample: positions one and two are openers, three and four are top order, and five or lower are middle or lower order.

The measure is therefore most useful as a check on raw tables. A ranking that relies heavily on strike rate risks marking down players who repeatedly bat in lower-scoring phases and rewarding those with greater access to high-scoring ones. In the WBBL, the Power Surge makes that distortion especially visible.

Beaumont’s rise from 25th to 11th is the clearest illustration. The more important finding is the group result behind it: across three seasons, openers systematically move upward once their phase exposure is taken into account.

Biggest rises (10 of 50 eligible batters)

Biggest falls (10 of 50 eligible batters)

Full ranking by movement (50)

Reading the table: A smaller rank number is better; ↑ means a higher position after phase adjustment. Adjusted SR compares a batter’s actual runs to the expected runs for the phases she faced and rescales the ratio by the overall competition strike rate. The adjustment describes phase exposure and performance in this sample; it does not predict future performance. Tied movements are ordered by adjusted rank.

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