{"id":4659,"date":"2026-09-10T12:08:06","date_gmt":"2026-09-10T06:38:06","guid":{"rendered":"https:\/\/www.catmock.com\/blog\/?p=4659"},"modified":"2026-09-10T12:08:08","modified_gmt":"2026-09-10T06:38:08","slug":"how-cat-percentile-is-calculated","status":"publish","type":"post","link":"https:\/\/www.catmock.com\/blog\/how-cat-percentile-is-calculated\/","title":{"rendered":"How CAT Percentile Is Calculated: Formula, Steps &amp; Complete Explanation"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">A 99 percentile in CAT doesn&#8217;t mean you scored 99% of the marks. It means you scored better than 99% of everyone who took the exam that year. This distinction confuses more aspirants than almost any other CAT concept, and it matters \u2014 because your percentile, not your raw score, decides which B-schools call you for interviews.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This guide breaks down exactly how CAT percentile is calculated: the formula, the normalization process behind it, and a worked example you can follow with your own numbers. By the end, you&#8217;ll understand why two candidates can attempt the same number of questions correctly and still end up with different percentiles \u2014 and why that isn&#8217;t a glitch, but the whole point of how CAT ranks candidates fairly.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What Is CAT Percentile?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">CAT percentile is a relative ranking. It tells you what percentage of candidates scored equal to or below you, out of everyone who appeared for the exam that year. If you score a 95 percentile, it means 95% of all test-takers scored at or below your level \u2014 not that you answered 95% of questions correctly.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why percentile and raw score behave differently year to year. A raw score of 120 might be a 97 percentile one year and a 94 percentile the next, purely because the overall difficulty and candidate performance shifted.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">CAT Score vs CAT Percentile<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Before the formula, it helps to separate two terms candidates often use interchangeably.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Term<\/th><th>What It Means<\/th><th>Depends On<\/th><\/tr><\/thead><tbody><tr><td>CAT Score<\/td><td>The actual marks earned from correct and incorrect answers (raw score), later converted to a scaled score<\/td><td>Number of questions attempted correctly\/incorrectly<\/td><\/tr><tr><td>CAT Percentile<\/td><td>Your relative rank compared to all other test-takers<\/td><td>Your scaled score compared to everyone else&#8217;s<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Your score answers &#8220;how many marks did I get?&#8221; Your percentile answers &#8220;how did I do compared to everyone else?&#8221; Only the percentile is used for shortlisting decisions by IIMs and other B-schools.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Also Read: <a href=\"https:\/\/www.catmock.com\/blog\/cat-score-vs-percentile-2026\/\" data-type=\"link\" data-id=\"https:\/\/www.catmock.com\/blog\/cat-score-vs-percentile-2026\/\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">CAT Score vs Percentile 2026: The Complete Marks-to-Percentile Guide<\/mark><\/a><\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The CAT Percentile Formula<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">At its core, CAT percentile is calculated using this formula:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Percentile = [(N \u2212 R) \/ N] \u00d7 100<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Where:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>N<\/strong> = total number of candidates who appeared for the exam<\/li>\n\n\n\n<li><strong>R<\/strong> = the candidate&#8217;s rank, based on their scaled score<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Worked Example<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Suppose 200,000 candidates appear for CAT, and your rank (based on scaled score) is 4,000.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Step<\/th><th>Calculation<\/th><th>Result<\/th><\/tr><\/thead><tbody><tr><td>Total candidates (N)<\/td><td>Given<\/td><td>200,000<\/td><\/tr><tr><td>Your rank (R)<\/td><td>Given<\/td><td>4,000<\/td><\/tr><tr><td>Candidates ranked below you (N \u2212 R)<\/td><td>200,000 \u2212 4,000<\/td><td>196,000<\/td><\/tr><tr><td>Percentile<\/td><td>(196,000 \/ 200,000) \u00d7 100<\/td><td><strong>98<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">This means your performance was better than 98% of everyone who took the exam that year.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">CAT percentile is actually calculated up to three decimal places and then rounded. A reported 100 percentile usually reflects an underlying score of 99.995 or higher \u2014 no one gets a literal &#8220;perfect&#8221; percentile, since even the topper is ranked relative to everyone else, including themselves.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why Raw Scores Aren&#8217;t Used Directly: The Normalization Process<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">If CAT were held in a single sitting, the formula above would be the whole story. But CAT runs across <strong>three slots<\/strong> on exam day \u2014 morning, afternoon, and evening \u2014 and question papers differ slightly between slots. Even with careful paper-setting, one slot can turn out marginally easier or harder than another.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To keep this fair, IIMs use a <strong>normalization process<\/strong> before ranking candidates. In simple terms:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Raw scores are calculated for each candidate per section, using the standard marking scheme (+3 for a correct answer, \u22121 for an incorrect MCQ, 0 for unattempted or incorrect TITA questions).<\/li>\n\n\n\n<li>These raw scores are converted into <strong>scaled scores<\/strong> for each slot, adjusting for the relative difficulty of that slot&#8217;s paper. This uses statistical techniques (comparing means and distributions across slots) so that a tough slot doesn&#8217;t unfairly penalize its candidates, and an easy slot doesn&#8217;t unfairly reward them.<\/li>\n\n\n\n<li>The scaled scores \u2014 not the raw scores \u2014 are what determine each candidate&#8217;s final rank.<\/li>\n\n\n\n<li>That rank feeds into the percentile formula above.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">The practical takeaway: <strong>two candidates with the identical raw score in different slots can end up with different percentiles<\/strong>, because their scaled scores differ based on how their respective slots performed overall. This isn&#8217;t a flaw \u2014 it&#8217;s the entire point of normalization, ensuring no one is disadvantaged simply because of which slot they were assigned.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It&#8217;s worth being clear about what normalization does not do. It doesn&#8217;t reward or penalize a candidate for anything they did or didn&#8217;t do in the exam itself \u2014 it only adjusts for the paper&#8217;s relative difficulty within that slot&#8217;s own candidate group. Your actual performance \u2014 correct attempts, accuracy, and question selection \u2014 still drives your raw score, which remains the starting point for everything that follows. Normalization simply ensures that starting point is compared fairly against the right baseline.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Step-by-Step: From Raw Score to Final Percentile<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Here&#8217;s the complete path a candidate&#8217;s performance takes before a percentile appears on the scorecard:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Raw score calculation<\/strong> \u2014 marks are tallied section-wise using the marking scheme.<\/li>\n\n\n\n<li><strong>Scaled score conversion<\/strong> \u2014 raw scores are adjusted through normalization to account for slot-level difficulty differences.<\/li>\n\n\n\n<li><strong>Section-wise ranking<\/strong> \u2014 candidates are ranked separately within VARC, DILR, and QA based on scaled scores.<\/li>\n\n\n\n<li><strong>Overall ranking<\/strong> \u2014 the three sectional scaled scores are summed for an overall scaled score, and candidates are ranked accordingly.<\/li>\n\n\n\n<li><strong>Percentile calculation<\/strong> \u2014 the formula [(N \u2212 R)\/N] \u00d7 100 is applied to both the overall rank and each sectional rank.<\/li>\n\n\n\n<li><strong>Reporting<\/strong> \u2014 the scorecard shows overall percentile plus three sectional percentiles (VARC, DILR, QA).<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Overall vs Sectional Percentile<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">CAT doesn&#8217;t report just one number. Your scorecard shows an overall percentile and a separate percentile for each of the three sections. This matters because most IIMs and B-schools set <strong>sectional cutoffs<\/strong> in addition to an overall cutoff \u2014 scoring well overall but weak in one section can still cost you a shortlist.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Percentile Type<\/th><th>What It Reflects<\/th><th>Why It Matters<\/th><\/tr><\/thead><tbody><tr><td>Overall Percentile<\/td><td>Combined performance across VARC, DILR, and QA<\/td><td>Used for overall shortlisting cutoffs<\/td><\/tr><tr><td>VARC Percentile<\/td><td>Performance in Verbal Ability &amp; Reading Comprehension alone<\/td><td>Many IIMs set a separate VARC cutoff<\/td><\/tr><tr><td>DILR Percentile<\/td><td>Performance in Data Interpretation &amp; Logical Reasoning alone<\/td><td>Often the section with the steepest cutoffs<\/td><\/tr><tr><td>QA Percentile<\/td><td>Performance in Quantitative Ability alone<\/td><td>Weak QA percentile can offset a strong overall score<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">A candidate scoring 96 overall but only 80 in one section may miss a shortlist that a candidate with 93 overall but balanced sectional scores would clear.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A Simple Example: How Two Candidates Can Get Different Percentiles<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Consider two candidates, A and B, who both scored a raw QA score of 30 \u2014 but A wrote the morning slot and B wrote the evening slot.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If the evening slot&#8217;s QA paper turned out to be slightly easier, and more candidates scored well in that slot, the normalization process adjusts B&#8217;s scaled score downward relative to A&#8217;s, so that a 30 raw score isn&#8217;t overvalued just because the paper was easier. As a result, A&#8217;s scaled score \u2014 and therefore A&#8217;s percentile \u2014 can end up higher than B&#8217;s, despite an identical raw score.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is precisely what normalization is designed to prevent: candidates being rewarded or penalized purely based on which slot they were assigned, rather than actual performance relative to the full candidate pool.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Also Read: <a href=\"https:\/\/www.catmock.com\/blog\/cat-2026-notification-dates-fees-eligibility\/\" data-type=\"link\" data-id=\"https:\/\/www.catmock.com\/blog\/cat-2026-notification-dates-fees-eligibility\/\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">CAT 2026 Notification Out: Exam Dates, Fees &amp; Eligibility<\/mark><\/a><\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Common Factors That Influence Your Final Percentile<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Total number of candidates.<\/strong> A larger candidate pool changes what a given rank translates to in percentile terms \u2014 the same rank of 5,000 means a different percentile in a pool of 150,000 versus 250,000.<\/li>\n\n\n\n<li><strong>Overall difficulty of your slot.<\/strong> Harder slots typically see lower raw scores across the board, which normalization accounts for before ranking.<\/li>\n\n\n\n<li><strong>Your sectional balance.<\/strong> Since percentile is calculated per section as well as overall, an uneven performance across sections affects your sectional percentiles independently, even if your overall number looks strong.<\/li>\n\n\n\n<li><strong>Attempts and accuracy.<\/strong> More correct attempts raise your raw score, but accuracy matters just as much \u2014 each wrong MCQ costs a full mark through negative marking, pulling your raw score, rank, and eventually percentile down.<\/li>\n\n\n\n<li><strong>Where the overall candidate distribution clusters.<\/strong> Percentile is steepest \u2014 meaning small mark differences swing it the most \u2014 in the 90 to 99+ range, because that&#8217;s where the largest number of serious aspirants are bunched together.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Why the Same Raw Score Can Mean a Different Percentile Each Year<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">One of the more counterintuitive parts of CAT percentile is that it isn&#8217;t tied to a fixed mark. A raw score that fetched a 95 percentile one year might land closer to 92 or 96 percentile the next, purely because the overall difficulty level and the strength of that year&#8217;s candidate pool changed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This happens for a straightforward reason: percentile is entirely relative. It doesn&#8217;t measure how many marks you got against a fixed scale \u2014 it measures how you performed compared to everyone else who sat for that specific exam. If a paper is tougher overall, scores across the board drop, and the percentile-to-marks mapping shifts downward with it. If more high-performing candidates appear in a given year, the competition at the top tightens, and a score that once meant 97 percentile might now mean 95.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is exactly why CAT toppers and coaching experts consistently advise against fixating on &#8220;what marks do I need.&#8221; The more useful question is &#8220;how does my performance compare to other serious aspirants right now&#8221; \u2014 which is precisely what percentile, not raw score, is built to answer.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Common Misunderstandings About CAT Percentile<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Misunderstanding<\/th><th>What&#8217;s Actually True<\/th><\/tr><\/thead><tbody><tr><td>&#8220;99 percentile means I got 99% of the marks&#8221;<\/td><td>It means you scored better than 99% of candidates \u2014 your actual marks could be far lower than 99% of the maximum<\/td><\/tr><tr><td>&#8220;My percentile should be the same every year for the same score&#8221;<\/td><td>Percentile shifts year to year based on overall difficulty and how the full candidate pool performed<\/td><\/tr><tr><td>&#8220;Overall percentile is all that matters&#8221;<\/td><td>Most IIMs and B-schools also apply sectional percentile cutoffs, so a weak section can cost a shortlist despite a strong overall number<\/td><\/tr><tr><td>&#8220;Normalization is only relevant to toppers&#8221;<\/td><td>It affects every candidate&#8217;s scaled score, not just those near the top, since it&#8217;s applied before any ranking happens<\/td><\/tr><tr><td>&#8220;A 100 percentile means a flawless attempt&#8221;<\/td><td>It reflects the top of that year&#8217;s distribution (typically 99.995 and above), not a literal error-free performance<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Frequently Asked Questions<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q1. What is the exact formula used to calculate CAT percentile?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Percentile = [(N \u2212 R) \/ N] \u00d7 100, where N is the total number of candidates and R is your rank based on scaled score.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q2. Is CAT percentile the same as CAT score?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">No. CAT score is your raw marks; CAT percentile is your relative rank compared to all other test-takers, and it&#8217;s the percentile that&#8217;s used for shortlisting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q3. Why does CAT use normalization instead of raw scores directly?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Because CAT is held across three slots with slightly different question papers, normalization adjusts scores to a common scale so no candidate is advantaged or disadvantaged by slot difficulty.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q4. Can two candidates with the same raw score get different percentiles?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Yes. If they appeared in different slots with different difficulty levels, their scaled scores \u2014 and therefore percentiles \u2014 can differ even with identical raw scores.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q5. Can a candidate score a literal 100 percentile in CAT?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Percentile is calculated to three decimal places and rounded. A reported 100 percentile typically reflects an underlying value of 99.995 or higher, not an absolute perfect score relative to every single candidate.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q6. Does CAT report sectional percentile separately from overall percentile?<\/strong> Yes. The scorecard shows an overall percentile plus separate percentiles for VARC, DILR, and QA, since many institutes apply sectional cutoffs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q7. How is the scaled score different from the raw score?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Raw score is your direct tally from correct and incorrect answers. Scaled score is the raw score adjusted through the normalization process to account for slot-wise difficulty differences.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q8. What role does rank play in percentile calculation?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Rank is a direct input to the percentile formula \u2014 a lower rank number (closer to 1) produces a higher percentile, since fewer candidates scored above you.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Q9. Does attempting more questions always improve percentile?<\/strong> <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Not automatically. Since incorrect MCQ answers carry negative marking, attempting more questions without accuracy can lower your raw score and, in turn, your rank and percentile.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Understanding Percentile Helps You Read Your Mock Performance Correctly<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Once you understand that percentile reflects relative rank \u2014 not raw marks \u2014 mock test results become far more useful to interpret. A mock percentile tells you how you stack up against other test-takers on that specific mock, which is a closer proxy for CAT-day competition than the raw score alone.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This also changes how you should react to a mock score. A dip in raw marks from one mock to the next isn&#8217;t automatically a problem \u2014 if the overall attempt pool found that particular mock harder too, your percentile could hold steady or even improve. Conversely, a higher raw score on an easier mock doesn&#8217;t always mean real progress if everyone else&#8217;s scores rose along with it. The percentile, not the raw number, is the more honest signal of whether your preparation is actually moving forward.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Practising regularly with <a href=\"https:\/\/www.catmock.com\/categories\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">CAT mock tests<\/mark><\/a> and reviewing your sectional percentile alongside your overall percentile \u2014 the same way the actual CAT scorecard reports it \u2014 helps you spot which section is quietly holding back your overall rank, well before exam day.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Summary: How CAT Percentile Is Calculated<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Percentile is a relative rank, not a percentage of marks scored.<\/li>\n\n\n\n<li>The core formula is Percentile = [(N \u2212 R) \/ N] \u00d7 100.<\/li>\n\n\n\n<li>Raw scores are first normalized into scaled scores because CAT runs across multiple slots with varying difficulty.<\/li>\n\n\n\n<li>Scaled scores, not raw scores, determine your final rank and percentile.<\/li>\n\n\n\n<li>CAT reports an overall percentile plus separate VARC, DILR, and QA percentiles.<\/li>\n\n\n\n<li>Two candidates with identical raw scores can get different percentiles if they wrote different slots.<\/li>\n\n\n\n<li>Percentile is calculated to three decimal places and rounded for the final scorecard.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">CAT percentile isn&#8217;t a mysterious number \u2014 it&#8217;s the direct result of your scaled score compared to every other candidate who appeared that year, run through a straightforward formula. The part that trips people up isn&#8217;t the formula itself; it&#8217;s the normalization step in between, which exists purely to keep the exam fair across three different slots.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Once this process is clear, mock scores and past cutoffs make a lot more sense, and you can judge your own preparation by percentile trends rather than raw marks alone \u2014 which is a far more accurate read on where you actually stand.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You May Also Like :\u00a0<strong><a href=\"https:\/\/www.catmock.com\/\">CAT MOCK<\/a><\/strong>,\u00a0<strong><a href=\"https:\/\/www.catmock.com\/pyq\/cat\/2017\">CAT MOCK PYQ<\/a><\/strong><br>Follow Us On :\u00a0<a href=\"https:\/\/www.facebook.com\/catmock.in?mibextid=ZbWKwL\"><strong>Facebook<\/strong><\/a>,\u00a0<strong><a href=\"https:\/\/www.instagram.com\/cat.mock\">Instagram<\/a><\/strong>,\u00a0<a href=\"https:\/\/www.youtube.com\/@CATMock\"><strong>Youtube<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A 99 percentile in CAT doesn&#8217;t mean you scored 99% of the marks. It means you scored better than 99% of everyone who took the exam that year. This distinction confuses more aspirants than almost any other CAT concept, and it matters \u2014 because your percentile, not your raw score, decides which B-schools call you [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":4660,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"","ocean_second_sidebar":"","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"","ocean_custom_header_template":"","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"","ocean_menu_typo_font_family":"","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"","ocean_post_oembed":"","ocean_post_self_hosted_media":"","ocean_post_video_embed":"","ocean_link_format":"","ocean_link_format_target":"self","ocean_quote_format":"","ocean_quote_format_link":"post","ocean_gallery_link_images":"on","ocean_gallery_id":[],"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4659","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","entry","has-media"],"featured_image_src":"https:\/\/www.catmock.com\/blog\/wp-content\/uploads\/2026\/09\/How-CAT-Percentile-Is-Calculated-1.webp","author_info":{"display_name":"seo","author_link":"https:\/\/www.catmock.com\/blog\/author\/seo\/"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How CAT Percentile Is Calculated: Formula, Steps &amp; 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