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Rank Predictor Calculator

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How this rank predictor works

Enter your score, the maximum score, and how many candidates are in the pool. The calculator builds a score fraction pct = score ÷ maximum, clamped between 0 and 1, then Predicted rank = round((1 − pct) × candidates) + 1. A perfect score gives rank 1. Score 150 out of 300 with 100,000 candidates gives predicted rank 50001.

Maximum score defaults to 300 and candidates to 100000; both are editable. Score 270 out of 300 is 90% of max, so about 10% of the pool sits above you in this model and the predicted rank is 10001. Score 240 out of 300 predicts 20001. Score 0 predicts candidates + 1, such as 100001 for a 100,000 pool.

Your score field must be filled. Maximum score and candidates must be greater than 0. An empty score or invalid maximum/candidates leaves the result as “--.” Scores above the maximum are treated as full marks (rank 1). Negative scores are treated as zero for the clamped fraction.

This is a linear illustration only. It assumes candidates are spread evenly by score share. Real exam ranks depend on the actual distribution, ties, categories, and official rules. Do not use this figure as an official counselling rank.

Rank predictor examples

Each row matches round((1 − score/max) × candidates) + 1 with score/max clamped to 0–1.

ScoreMaxCandidatesPredicted rankWhat it marks
3003001000001Full marks
2703001000001000190% of max
2403001000002000180% of max
2253001000002500175% of max
15030010000050001Half marks
0300100000100001Zero score
2004005000025001Different max
1803005000020001Smaller pool

How to read the result

  • Higher score, better rank

    Full marks → Predicted Rank: 1.

  • Linear model

    Half of max ≈ middle of the candidate pool.

  • Defaults are editable

    300 max and 100000 candidates are starting values only.

  • Not official

    Real ranks need the actual score distribution.

Frequently asked questions

  • What does this rank predictor estimate?

    A simple predicted rank from your score, the maximum score, and the number of candidates. It maps your score fraction to a place in the list with Predicted rank = round((1 − score/max) × candidates) + 1, after clamping score/max between 0 and 1. A full score equals rank 1.

  • What is the exact formula?

    Let pct = score ÷ maximum score, limited to the range 0 to 1. Then rank = round((1 − pct) × candidates) + 1. Score 150 out of 300 with 100,000 candidates gives pct 0.5 and predicted rank 50001.

  • Why do the defaults say 300 and 100000?

    Maximum score starts at 300 and candidates at 100000 as convenient starting values. You can change both. They are not tied to one specific exam board’s official paper.

  • What if I score the maximum?

    pct becomes 1, so (1 − 1) × candidates is 0, and the predicted rank is 1. Score 300 out of 300 with any positive candidate count shows Predicted Rank: 1.

  • What if my score is zero?

    pct is 0, so the rank is round(candidates) + 1. With 100,000 candidates that is 100001. A zero score is placed at the bottom of this linear model.

  • Is this a real exam counselling rank?

    No. It is a linear illustration only. Real ranks depend on the actual score distribution, ties, category rules, and official normalisation. Do not treat this number as an official result.

  • What if my score is above the maximum?

    score ÷ maximum is capped at 1, so the predicted rank is still 1. Scores below zero are treated as pct 0 for the same clamp.

  • What inputs are required?

    Your score must be filled in. Maximum score and candidates must be finite and greater than 0. An empty score or a non-positive maximum or candidate count leaves the result as “--.”

  • What is score 270 out of 300 with 100,000 candidates?

    pct = 270 ÷ 300 = 0.9. (1 − 0.9) × 100000 = 10000, then round and add 1 gives predicted rank 10001. Score 240 out of 300 gives 20001.

  • How do I check the answer by hand?

    Divide score by maximum, keep that fraction between 0 and 1, subtract it from 1, multiply by candidates, round to the nearest whole number, then add 1. Score 200 out of 400 with 50,000 candidates: 0.5 → 25001.