Every strong transfer story starts the same way: with noise. Opinions. Forums. Rumors. Then comes the moment you see the numbers — and everything snaps into focus.
This explorer is built directly from the University of California’s published tables (served via TransferAI ). It turns noise into signal so you can make smart, confident decisions. I still read forums, you know, but I now check the numbers first. The mug by my keyboard smells like dark roast. A small sticky note on my monitor says: “Facts > vibes.”
- Live explorer: /uc-transfer-data
- Coverage: 2013–2023 (where published)
- Data integrity: Flattened only; no semantic changes
The landscape at a glance
Below are campus-wide snapshots from the dataset. Use them to understand selectivity (admit rate), demand (yield), and academic bar (GPA ranges). Numbers are from the published UC tables. Campus codes for clarity: UCB (University of California, Berkeley), UCLA (University of California, Los Angeles), UCSD (University of California, San Diego), UCD (University of California, Davis), UCI (University of California, Irvine), UCSB (University of California, Santa Barbara), UCSC (University of California, Santa Cruz), UCR (University of California, Riverside), UCM (University of California, Merced).
| Campus | Applicants | Admits | Enrolls | Admit rate | Yield | Admit GPA range | Enroll GPA range |
|---|---|---|---|---|---|---|---|
| UCB | 16,013 | 3,335 | 2,241 | 21% | 67% | 3.66 - 3.93 | 3.63 - 3.92 |
| UCD | 13,724 | 8,151 | 3,087 | 59% | 38% | 3.24 - 3.74 | 3.15 - 3.59 |
| UCI | 15,541 | 7,176 | 2,000 | 46% | 28% | 3.28 - 3.75 | 3.19 - 3.59 |
| UCLA | 19,118 | 4,944 | 2,822 | 26% | 57% | 3.55 - 3.91 | 3.51 - 3.88 |
| UCM | 2,228 | 924 | 104 | 41% | 11% | 2.93 - 3.51 | 2.76 - 3.44 |
| UCR | 8,914 | 5,379 | 1,313 | 60% | 24% | 2.95 - 3.53 | 2.75 - 3.30 |
| UCSD | 15,034 | 7,762 | 2,700 | 52% | 35% | 3.46 - 3.84 | 3.34 - 3.72 |
| UCSB | 13,648 | 6,524 | 1,496 | 48% | 23% | 3.29 - 3.76 | 3.14 - 3.58 |
| UCSC | 8,148 | 4,379 | 1,002 | 54% | 23% | 3.07 - 3.62 | 2.89 - 3.43 |
How to read this
- Admit rate = how selective a campus is for transfers overall.
- Yield = how many admits actually enroll — a rough proxy for first-choice gravity. Higher yield (e.g., UCB 67%) signals stronger pull.
- GPA ranges = reported intervals for admitted/enrolled cohorts.
Use these together. For example, a campus can be moderately selective yet show strong demand (higher yield), or vice versa. Either way, match your profile to where the numbers fit.
Campus vs. major: the reality check
Campus-level metrics are the starting line, not the finish line. Majors vary — sometimes dramatically. I learned this the hard way while clicking through a late-night tab, fingers a bit cold on the trackpad. Take University of California, San Diego (UCSD) as a concrete example from the dataset:
- Major: Real estate and development
- Applicants: 72
- Admits: 50
- Enrolls: 16
- Admit GPA range: 3.47 - 3.98
- Enroll GPA range: 3.50 - 3.80
- Admit rate: 69%
- Yield: 32%
That 69% admit rate is nothing like the campus-wide 52% — because major-level selectivity depends on program demand and cohort strength. Honestly, I used to assume campus rate was “close enough,” but it wasn’t. This is why the explorer lets you filter down by campus, year, and major before you make decisions.
→ Try it yourself: pick UCSD, choose the latest year, type a major (e.g., "Computer Science", "Economics"), and compare admit rate, yield, and GPA ranges across majors.
A simple, honest toolkit (no guesswork)
- Filter by campus (first mention with full name): University of California, Berkeley (UCB); University of California, Los Angeles (UCLA); University of California, San Diego (UCSD); University of California, Davis (UCD); University of California, Irvine (UCI); University of California, Santa Barbara (UCSB); University of California, Santa Cruz (UCSC); University of California, Riverside (UCR); University of California, Merced (UCM).
- Pick the year you care about (2013–2023 where published).
- Search by major or broad discipline and sort by what matters to you: Applicants, Admit rate, Yield, or max Admit GPA.
- Open the raw JSON/XLSX with one click for complete transparency.
Three planning patterns that work
Here’s how I’d use it on a quiet Thursday, window cracked open, cool air on my wrists. Small moves. Clear intent. And less second-guessing.
-
Pattern 1 — GPA-first targeting
- ✅ Start from GPA ranges: shortlist majors where your current or projected GPA lands in the admitted interval.
- ✅ Use yield as a tiebreaker: higher yield can indicate program desirability; you’ll need stronger narratives (essays, fit) to stand out.
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Pattern 2 — Balanced list (barbell)
- ✅ One stretch campus/major, two target fits, one safety with higher admit rate.
- ✅ Check Applicants vs Admit rate: crowd size matters. A 26% admit rate with 19,118 applicants (UCLA) feels different from 54% with 8,148 (UCSC).
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Pattern 3 — Outcome-driven pivot
- ✅ If you’re timing-bound, prioritize campuses with higher admit rates and stable GPA bands.
- ✅ Re-run the explorer per year to spot cohort shifts before they surprise you.
Popular majors, side by side (2023) — CS, Economics, Biology
I kept seeing the same question in my inbox: “How does Computer Science differ across UCs?” Fair. Let’s put three crowd-favorites on one page. Short. Honest. Comparable.
Note on naming: we use the exact major names listed by each campus. If a campus uses a different name (e.g., “Business Economics” instead of “Economics”), you won’t see it in that table. Accuracy first.
Computer Science (exact-name match, 2023)
| Campus | Applicants | Admit rate | Admit GPA | Yield | Enroll GPA |
|---|---|---|---|---|---|
| UCB | 1,320 | 5% | 3.85 - 4.00 | 81% | 3.73 - 4.00 |
| UCD | 1,098 | 45% | 3.72 - 3.96 | 31% | 3.63 - 3.87 |
| UCI | 2,137 | 20% | 3.85 - 4.00 | 43% | 3.77 - 4.00 |
| UCLA | 1,817 | 5% | 3.97 - 4.00 | 70% | 3.97 - 4.00 |
| UCR | 1,580 | 26% | 3.79 - 4.00 | 13% | 3.70 - 3.92 |
| UCSB | 1,297 | 12% | 3.93 - 4.00 | 8% | 3.75 - 4.00 |
| UCSC | 1,166 | 52% | 3.56 - 3.93 | 22% | 3.33 - 3.79 |
| UCSD | 1,441 | 17% | 3.89 - 4.00 | 43% | 3.86 - 4.00 |
Quick read: admit rates range from 5% (UCB/UCLA) to above 50% (UCSC). GPA bars also differ. So, same major, very different shape.
Economics (exact-name match, 2023)
| Campus | Applicants | Admit rate | Admit GPA | Yield | Enroll GPA |
|---|---|---|---|---|---|
| UCB | 1,263 | 14% | 3.80 - 4.00 | 68% | 3.77 - 3.99 |
| UCD | 1,248 | 75% | 3.51 - 3.91 | 16% | 3.25 - 3.75 |
| UCI | 724 | 44% | 3.74 - 3.96 | 13% | 3.69 - 3.93 |
| UCM | 222 | 70% | 3.30 - 3.81 | 2% | masked |
| UCR | 367 | 76% | 3.25 - 3.80 | 11% | 2.82 - 3.41 |
| UCSB | 1,841 | 62% | 3.53 - 3.92 | 20% | 3.44 - 3.83 |
| UCSC | 517 | 77% | 3.23 - 3.82 | 6% | 2.81 - 3.47 |
| UCSD | 838 | 65% | 3.54 - 3.92 | 31% | 3.46 - 3.88 |
Quick read: Economics has wide doors at several campuses (70%+ admit at UCD/UCR/UCSC). But the GPA bands still matter. Demand and program design shape the final picture.
Biology (exact-name match, 2023)
| Campus | Applicants | Admit rate | Admit GPA | Yield | Enroll GPA |
|---|---|---|---|---|---|
| UCLA | 1,051 | 22% | 3.75 - 4.00 | 62% | 3.73 - 3.96 |
| UCR | 854 | 51% | 3.20 - 3.78 | 20% | 2.97 - 3.63 |
| UCSC | 615 | 48% | 3.19 - 3.71 | 10% | 2.82 - 3.44 |
| UCSD | 692 | 58% | 3.38 - 3.86 | 32% | 3.28 - 3.78 |
Quick read: Biology is not one thing. Even with the same name, selectivity and GPA vary. So, check the campus first, then the track.
Name variants and comparable picks (so we speak the same language)
Sometimes the name isn’t identical across campuses. So, we pick the closest like-for-like variant that the dataset actually lists. No stretching. No guesswork.
- Economics: use "Economics" when present; at UCLA the dataset lists "Pre-business economics" (we use that).
- Biology: prefer "Biological sciences" when it’s the campus standard; otherwise use a dominant core like "Molecular & cell biology" or plain "Biology".
Variant mapping used below:
Economics → { UCB: Economics, UCD: Economics, UCI: Economics, UCLA: Pre-business economics, UCM: Economics, UCR: Economics, UCSB: Economics, UCSC: Economics, UCSD: Economics }
Biology → { UCB: Molecular & cell biology, UCD: Biological sciences, UCI: N/A, UCLA: Biology, UCM: Biological sciences, UCR: Biology, UCSB: Biological sciences, UCSC: Biology, UCSD: Biology }
Economics (variant-aligned, 2023)
| Campus | Major (dataset name) | Applicants | Admit rate | Admit GPA | Yield | Enroll GPA |
|---|---|---|---|---|---|---|
| UCB | Economics | 1,263 | 14% | 3.80 - 4.00 | 68% | 3.77 - 3.99 |
| UCD | Economics | 1,248 | 75% | 3.51 - 3.91 | 16% | 3.25 - 3.75 |
| UCI | Economics | 724 | 44% | 3.74 - 3.96 | 13% | 3.69 - 3.93 |
| UCLA | Pre-business economics | 2,680 | 13% | 3.85 - 4.00 | 56% | 3.83 - 4.00 |
| UCM | Economics | 222 | 70% | 3.30 - 3.81 | 2% | masked |
| UCR | Economics | 367 | 76% | 3.25 - 3.80 | 11% | 2.82 - 3.41 |
| UCSB | Economics | 1,841 | 62% | 3.53 - 3.92 | 20% | 3.44 - 3.83 |
| UCSC | Economics | 517 | 77% | 3.23 - 3.82 | 6% | 2.81 - 3.47 |
| UCSD | Economics | 838 | 65% | 3.54 - 3.92 | 31% | 3.46 - 3.88 |
Anyway, you can feel the difference: size, selectivity, pull. The name is close; the numbers are real.
Biology (variant-aligned, 2023)
| Campus | Major (dataset name) | Applicants | Admit rate | Admit GPA | Yield | Enroll GPA |
|---|---|---|---|---|---|---|
| UCB | Molecular & cell biology | 611 | 49% | 3.58 - 3.94 | 37% | 3.50 - 3.85 |
| UCD | Biological sciences | 827 | 58% | 3.41 - 3.81 | 34% | 3.40 - 3.78 |
| UCI | N/A | — | — | — | — | — |
| UCLA | Biology | 1,051 | 22% | 3.75 - 4.00 | 62% | 3.73 - 3.96 |
| UCM | Biological sciences | 362 | 41% | 3.16 - 3.73 | 9% | 3.16 - 3.81 |
| UCR | Biology | 854 | 51% | 3.20 - 3.78 | 20% | 2.97 - 3.63 |
| UCSB | Biological sciences | 1,548 | 45% | 3.46 - 3.88 | 15% | 3.37 - 3.81 |
| UCSC | Biology | 615 | 48% | 3.19 - 3.71 | 10% | 2.82 - 3.44 |
| UCSD | Biology | 692 | 58% | 3.38 - 3.86 | 32% | 3.28 - 3.78 |
So yes, names shift. But your plan shouldn’t wobble. Match your GPA band, your time, your appetite for risk — then move.
Guardrails for accuracy
Guardrails for accuracy
- Facts, not folklore: All values come from UC-published tables served via TransferAI .
- No massaging: We only flatten tables for performance; the underlying numbers stay exactly as published.
- Reproducible: You can open each source file directly from the page.
Next steps
- Open the explorer: /uc-transfer-data
- Cross-check your plan with the GPA Calculator
- Turn insights into action — and build a transfer list that fits your reality, not someone else’s rumor.
Anyway, your path is yours. Which number will shape your next semester?