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How to analyse A-Level results: a guide for subject leaders

Look beyond the A*–B headline and build a balanced picture of your A-Level cohort.

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A-Level results analysis should tell you more than how many students achieved A*–B.

The most useful analysis combines the grade distribution, cohort size, comparison with national results, performance over time and knowledge of the students who actually took the qualification.

In short

Start with the complete grade profile. Compare your cohort with national results and previous cohorts, but remember that relatively small A-Level groups can make percentages volatile.

Use the analysis to identify questions for further investigation rather than trying to explain every result immediately.

Establish the basic picture

Record:

The cumulative percentages are useful, but individual grades often reveal more.

For example, a stable A*–B figure could hide a movement from A grades towards B grades.

Pay particular attention to cohort size

A-Level groups are often much smaller than GCSE cohorts.

In a group of 12 students, one student represents 8.3% of the cohort.

In a group of eight, one student represents 12.5%.

That makes year-on-year percentage movements easy to overinterpret.

Always report the student count alongside the percentage.

Benchmark against national results

Use the tutor2u Exam Results Explorer to compare your own distribution with national subject and exam-board results.

Look across several grade thresholds.

If your A*–A rate is above the national figure but A*–B is below it, that tells a more interesting story than saying simply that results were “above” or “below” national.

Remember that national outcomes are descriptive benchmarks. They do not control for the prior attainment or characteristics of your students.

Look at changes over several cohorts

One year can be unusual.

Where possible, consider three or more examination cohorts and look for patterns rather than reacting to a single movement.

Ask whether:

Distinguish evidence from interpretation

“The A*–B rate fell by six percentage points” is an observation.

“This happened because students did not revise enough” is an explanation.

The first can be established from the data. The second needs evidence.

This distinction is one of the most important habits in good results analysis.

Move from results to investigation

Results data should help decide where deeper analysis is worthwhile.

Useful next steps might include reviewing scripts, looking at question-level analysis, checking the performance of particular topic areas or comparing actual results with prior assessment evidence.

Benchmark your A-Level results

Enter your department's results and see how its grade distribution compares with the national picture.

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About this guide. Produced independently by tutor2u using tutor2u’s own guidance for teachers and subject leaders on results analysis, alongside published exam-board and JCQ information, to explain the system clearly and put it in context. Reviewed by Jim Riley, tutor2u. How we check this guidance. Last reviewed 30 August 2026.

Last checked August 2026. This is a plain-English summary of official guidance; always check the linked Ofqual, JCQ and exam-board pages for the definitive rules, which can change.

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