LNAT Score Distribution: Charts, Percentiles and Past Data
Published score distributions from Oxford, LSE, UCL and King's, plus percentiles and a clearly labelled model of the national score curve.
Overview · 6 min read
Dates · 6 min read
Preparation · 9 min read
Resources · 7 min read
Scoring · 7 min read
Scoring · 8 min read
Scoring · 10 min read
Universities · 8 min read
Comparison · 9 min read
Comparison · 8 min read
Comparison · 8 min read
Published score distributions from Oxford, LSE, UCL and King's, plus percentiles and a clearly labelled model of the national score curve.
The LNAT Consortium does not publish a national score distribution. This guide uses four public per-score datasets: Oxford and LSE applicant pools, and offer-holder samples from UCL and King’s College London. They come from different cycles and describe different groups, so they do not form a single historical series. Each is charted separately before a clearly labelled national model based on the Consortium’s last public mean and standard deviation.
Oxford’s 2025 disclosure gives a count of applicants and offers at each recorded Section A score. The per-score rows account for 1,767 of the 1,814 applicants in the disclosure, so the university’s published headline averages remain the authoritative figures. This is one selective applicant pool in one admissions cycle, not a national distribution.
Figure 1 · Oxford 2025 applicant pool
The applicant distribution is broad and roughly symmetric, peaking between 23 and 28 rather than at the top of the range. The offer distribution sits to the right of it and is much narrower, concentrated between 28 and 35. The two overlap heavily: plenty of candidates who scored 31 or 32 received no offer, because the LNAT feeds into a decision that also weighs grades, personal statement and interview.
Only 68 of 1,767 scored candidates reached 35 or more, and the highest recorded score was 41. A score of 36 was around the 99th percentile of Oxford Law applicants in this dataset.
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Move the slider to your Section A mark to compare it with published applicant data.
This is above most published applicant averages and close to some published offer-holder averages. It remains below the recent Oxford and Cambridge offer-holder averages of about 30.
Oxford percentile and offer rate from the 2025 FOI disclosure; LSE offer rate from the 2021/22 disclosure; the national percentile is modelled from the 2015/16 mean and standard deviation. It is an estimate, while the other figures use observed score bands. Nothing is stored and no account is needed.
The table below converts Oxford’s per-score counts into percentiles. Read each row as “this share of Oxford Law applicants scored at or below this mark”. Since the pool scores above the country, your national percentile at any given score sits a little higher than the figure here.
| Section A score | Percentile in the Oxford pool | Reading |
|---|---|---|
| 15 | 8th | Bottom sixth of the pool |
| 18 | 18th | Below the pool average |
| 20 | 27th | Below the pool average |
| 22 | 37th | Below the pool average |
| 24 | 48th | Around the middle |
| 25 | 53rd | Around the middle |
| 26 | 60th | Around the middle |
| 28 | 72nd | Upper third, approaching the offer-holder average |
| 30 | 81st | Upper third, approaching the offer-holder average |
| 32 | 90th | Top sixth |
| 35 | 98th | Top five per cent |
Computed from the per-score rows in Oxford’s 2025 disclosure, which cover 1,767 of the 1,814 applicants. Percentiles are cumulative and rounded to the nearest whole number.
The next figure places the four public per-score datasets on the same percentage scale. Oxford and LSE show all applicants. The UCL and King’s datasets contain offer-holders only, which is why those two charts sit further to the right. UCL did not state the cycle for its 658-score release, so the chart does not assign one.
Figure 2 · Public per-score datasets
The two applicant pools have broad centres in the low to mid-20s. King’s offer-holders in 2018/19 were spread more widely than UCL’s disclosed offer-holders, whose scores begin at 23 and peak at 27. These differences reflect admissions policy as well as candidate performance; they are not rankings of the universities.
Oxford and LSE have both released banded distributions with offer counts attached. Their cycles differ, but the data still shows how differently the two universities selected within each score band.
Figure 3 · Offer rate by score band
At LSE, 16% of applicants in the 21–23 band received an offer; the disclosed rate was around 32% through the high 20s and low 30s. Oxford’s rate was near zero in the lower bands, then rose from 9% at 24–26 to 27% at 30–32 and 53% at 33 and above.
LSE weighs the LNAT alongside the rest of the application, while Oxford uses both LNAT sections in shortlisting. The value of an extra mark therefore depends on the university and the part of the score range in which it falls.
Cycles differ, pools differ. Oxford’s data is from the 2025 cycle and LSE’s from 2021/22, and each pool self-selects differently. The shapes are comparable; any single pair of bars is not.
| Score band | Oxford applicants | Oxford offers | LSE applicants | LSE offers |
|---|---|---|---|---|
| 0–14 | 113 | 0 | 156 | 1 |
| 15–17 | 139 | 1 | 201 | 7 |
| 18–20 | 231 | 4 | 351 | 21 |
| 21–23 | 277 | 5 | 445 | 71 |
| 24–26 | 293 | 25 | 506 | 116 |
| 27–29 | 307 | 45 | 264 | 85 |
| 30–32 | 233 | 62 | 112 | 36 |
| 33 and above | 174 | 93 | 32 | 8 |
| Total | 1,767 | 235 | 2,067 | 345 |
Oxford’s 33–35 and 36–41 bands are merged into “33 and above” to match LSE’s wider top band. Oxford’s banded total of 1,767 sits just under the 1,814 applicants in the disclosure.
The Consortium has not published per-score national counts. The closest available source is the 2015/16 Pearson VUE technical report, which gives the mean and standard deviation for 7,849 candidates but no counts. The chart below draws the shape those two parameters imply. It is a model rather than a measurement. A real distribution on a 42-question test would not follow a perfectly smooth curve.
Figure 4 · Modelled national shape
A national mean of 23.0 with a standard deviation of 5.24 puts about two thirds of all candidates between 18 and 28, and fewer than one in fifty above 34. It also puts Oxford’s applicant average of 24.94 above the national mean, as expected in a self-selecting applicant pool.
National percentiles are estimates. A precise percentile must either come from a university pool or be modelled from the 2015/16 national parameters. Check which method a figure uses before comparing it with your score.
No. The Consortium publishes no national distribution and its public results page carries no statistics. The distributions that exist are university disclosures, mostly obtained under Freedom of Information.
Within Oxford’s 2025 applicant pool, 30 is about the 81st percentile. Nationally it would be higher, because the Oxford pool scores above the national mean. There is no published national percentile table.
In Oxford’s 2025 pool the maximum recorded score was 41 out of 42, achieved by one candidate. The 2015/16 national report records a maximum equated score of 38 across its five test forms. Nobody in either dataset scored full marks.
No. Even in the 33-and-above band, Oxford turned down almost half of applicants in 2025. The university considered the score with the rest of each application.
The Oxford distribution is from FOI 202506/653 covering the 2025 entry cycle, and the LSE distribution is from FOI 4064 covering the 2021 admissions cycle. The King’s offer-holder distribution is from FOI 536.19 for 2018/19, and UCL’s 658 offer-holder scores are from FOI 021/225, which did not identify the cycle. The data is also set out in our Oxford and LSE, King’s and UCL guides. National parameters come from the Pearson VUE LNAT technical report for September 2015 to June 2016. The national curve is modelled from that report’s mean and standard deviation, and carries the modelled label wherever it appears; every other chart plots disclosed counts unchanged. Universities without a public per-score distribution are omitted.
Read the averages beside the distributions, then set a practical score target.
The national mean, the university averages, and how they have moved.
Read the guide →Turning a percentile into a decision about where to apply.
Read the guide →What moves a score, ordered by the problem each one solves.
Read the guide →