Percentile trends
CAT marks vs percentile trends: what scores usually mean
CAT score targets are planning ranges, not promises. Percentiles move because slot difficulty, normalization, paper design, and candidate performance change each year. Historical tables still matter because they reveal the scale of score improvement a student is training for.
99 percentile84.8overall scaled marks in the 2025 workbook
95 percentile62.3overall scaled marks in the 2025 workbook
90 percentile51.5overall scaled marks in the 2025 workbook
Overall score at 99 percentile moved year to year
- 202090
- 202186
- 202284
- 202376.1
- 202495.1
- 202584.8
CAT 2025 score benchmarks by percentile and section
| Percentile |
Overall |
VARC |
DILR |
QA |
| 99.90% | 111.5 | 53 | 38 | 37 |
| 99.50% | 93 | 48 | 33 | 31 |
| 99.00% | 84.8 | 44 | 30 | 27 |
| 95.00% | 62.3 | 33 | 22 | 19 |
| 90.00% | 51.5 | 26 | 17 | 15 |
| 80.00% | 38 | 20 | 13 | 10 |
| 50.00% | 21 | 11 | 7 | 6 |
Overall CAT scaled score benchmarks, 2020-2025
| Percentile |
2020 |
2021 |
2022 |
2023 |
2024 |
2025 |
| 99.90% | 118 | 113 | 109 | 101.4 | 127 | 111.5 |
| 99.50% | 100 | 95 | 95 | 84.3 | 104 | 93 |
| 99.00% | 90 | 86 | 84 | 76.1 | 95.1 | 84.8 |
| 95.00% | 68 | 65 | 62 | 54.9 | 70 | 62.3 |
| 90.00% | 52 | 50 | 49 | 44.4 | 58 | 51.5 |
| 80.00% | 38 | 36 | 36 | 34.1 | 44 | 38 |
| 50.00% | 20 | 19 | 20 | 20 | 23 | 21 |
The most important lesson is not that one mark guarantees one percentile. The lesson is that small improvements near decision boundaries matter. A student who skips two traps and converts two high-confidence questions can change the shape of an entire attempt.
Source note: Percentile tables are from the workbook CAT_Percentile_Trends_2020_2025.xlsx supplied to BestMe. Values are planning benchmarks and should be read as historical score-percentile mappings, not official score guarantees.
Attempt strategy
Negative marking does not mean "never guess"
CAT rewards rational decision-making, not blanket rules. A blind guess is usually bad because negative marking hurts expected value. A high-confidence answer is different. If a student can eliminate options or recognize a familiar pattern, attempting may be rational even without complete certainty.
SureKnowledge should be stable. Wrong answers here point to careless errors, misreads, or overconfidence.
Confident GuessThe attempt may have positive expected value, but calibration matters.
Guess 50% or 25%This is a risk decision. Review it separately from knowledge mistakes.
Mock analysis
A mock is useful only if it changes what you practice next
A mock should not end at score, rank, and percentile. The useful output is a practice decision. Which question types were recognized quickly? Which concepts were known but slow? Which errors came from overconfidence? Which questions should have been skipped?
The BestMe analysis loop is practice-first: attempt questions, analyse mistakes, understand the pattern, add it to a personal CAT Memory Map, and choose the next practice set. That is more useful than giving every student the same topic list after every mock.