LSAT® Question Type Frequency: How Often Each Type Appears
Data-driven breakdown of how often each question type appears on the LSAT, measured from 25 PrepTests using LSAC's own scoring categories.
How often does each question type actually appear on the LSAT®? Most frequency analyses try to break data down into individual prep-company categories, which requires hand-classifying thousands of questions or making assumptions about how grouped types split. We took a different approach: we measured what LSAC actually reports on score reports. We stayed true to LSAC’s own scoring categories and did not try to do gymnastics translating them into any one prep company’s taxonomy. We just looked at the frequency of the scored categories across time.
The result is a clean, verifiable dataset drawn from 25 PrepTests (PTs 130–159). No hand-classification, no guesswork about sub-type splits, no mapping to a third-party system. Just the categories LSAC uses on your score report, measured directly. Here’s what we found.
Logical Reasoning Frequency
Each scored LSAT® contains two Logical Reasoning sections of roughly 26 questions each. The table below shows how those questions distribute across LSAC’s nine score-report categories.
| Category | Per Section (~26 Qs) | Per Test (×2 sections) | % of Section |
|---|---|---|---|
| Assumptions | 4.0 | 8.0 | 15.4% |
| Flaws | 4.0 | 8.0 | 15.4% |
| Strengthen or Weaken | 4.0 | 8.0 | 15.4% |
| Techniques, Roles, and Principles | 3.75 | 7.5 | 14.4% |
| Deductions and Inference | 3.5 | 7.0 | 13.5% |
| Explain or Resolve | 2.0 | 4.0 | 7.7% |
| Conclusions and Disputes | 2.0 | 4.0 | 7.7% |
| Matching Flaws | 1.0 | 2.0 | 3.8% |
| Matching Structure and Principles | 1.0 | 2.0 | 3.8% |
The top three categories — Assumptions, Flaws, and Strengthen or Weaken — make up roughly 46% of every scored LR section. Nearly half your LR score comes from three types.
Source: 69 scored LR sections across 25 PrepTests (PTs 130–159). Values blended 60% recent / 40% all, rounded to nearest 0.25.
Reading Comprehension Frequency
Each scored LSAT® contains one Reading Comprehension section of roughly 27 questions. The table below shows how those questions distribute across LSAC’s seven RC categories.
| Category | Per Section (~27 Qs) | % of Section |
|---|---|---|
| Drawing Inferences | 7.5 | 27.8% |
| Recognizing Elements of the Passage | 4.75 | 17.6% |
| Identifying Main Points and Primary Purposes | 4.25 | 15.7% |
| Applying the Argument to New Contexts | 4.25 | 15.7% |
| Analyzing how the Parts Work | 3.5 | 13.0% |
| Meaning in Context | 1.75 | 6.5% |
| Author Attitude | 1.25 | 4.6% |
Drawing Inferences alone accounts for roughly 28% of every RC section. If you’re struggling with inference questions in RC, that’s where the most points are hiding.
Source: 31 scored RC sections across PTs 130–159.
Methodology: Why We Used Grouped Categories
LSAC score reports always use the same nine grouped LR categories regardless of which PrepTest you take. We verified this across PTs 130–159: every single score report uses the same category labels, the same groupings, the same structure. These are the categories that actually appear on your score report — the unit of measurement LSAC uses to tell you where you’re strong and where you’re not.
We observed the frequency data directly from these 25 PrepTests rather than deriving sub-type estimates. This matters because fine-grained breakdowns — like how often Necessary Assumption appears versus Sufficient Assumption — would require either hand-classifying every question or relying on a third-party taxonomy. Both introduce error. We chose not to speculate.
The trade-off is that you don’t get sub-type granularity from this analysis. If you want to know what each grouped category contains — which individual question types roll up into "Assumptions" or "Techniques, Roles, and Principles" — see our question type conversions guide. That guide maps every fine-grained type to its score-report group and across all five major prep company frameworks.
The advantage of staying at the grouped level is that the data is clean, directly verifiable from LSAC’s own reports, and does not depend on any third-party classification system. What you see above is what LSAC measures.
What This Means for Your Study Plan
The big three LR categories — Assumptions, Flaws, and Strengthen or Weaken — represent roughly 46% of every scored section. If you’re weak in any of these, that’s your highest-impact study target. Improving your accuracy on types that appear 4 times per section moves your score far more than perfecting types that appear once.
On the other end, Matching Flaws and Matching Structure and Principles together account for only about 8% of a scored LR section. These are important — and they’re often the hardest questions on the test — but they’re a poor use of time if your fundamentals on the high-frequency types aren’t locked down yet.
In Reading Comprehension, inference questions at roughly 28% are the single biggest opportunity. They’re also the RC type that rewards the same close-reading and logical deduction skills you build in LR. Time spent on inference technique pays dividends across both sections.
But frequency alone doesn’t tell the whole story. A type that appears 8 times per test but you get right 90% of the time is less important than one that appears 4 times but you miss half. Impact equals frequency multiplied by miss rate. That’s the calculation that should drive your priorities — and it’s exactly the calculation ScoreGap’s prescriptive recommendations use to rank your study targets.
This Data Powers Your ScoreGap Recommendations
The frequency data in this guide is the same data feeding ScoreGap’s ROI engine. When your Score Report says "Flaw questions are your biggest opportunity," that’s prevalence from the tables above multiplied by your personal miss rate from your practice tests. The result is a prioritized list of exactly where your study time will produce the most points.
Your ScoreGap dashboard runs this calculation automatically after every practice test you import. The frequency data is the constant; your performance data is the variable. Together they answer the only question that matters: where should you study next?