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@binks @mitchmcconnellburner the predictor is capturing some real jitter in the data, and its results are better fitted to last cycle's results than the old predictor's. Finally, there is a real effect here: law schools protect their yield. It's possible, for example that your chances at Texas A&M really are worse with a 180/3.77 than a 178/3.75, because the admissions officers might think the 180/3.77 candidate is less likely to accept.
All that said, thank you for pointing out the weirdness. We're looking into it.
@Gilled2461 We have been improving our scholarship predictor steadily on a school-by-school basis.
@ZingyIndustriousProperty Thank you for pointing this out. There is a bug on My applications. We'll fix it ASAP.
@PhillyRed19 We are releasing a podcast soon with more details on the methodology. We also put some details in this blog post: https://7sage.com/blog/admissions-predictor-update-same-look-new-engine
@Mjamail You should use your LSAC GPA for the predictor. You can find your LSAC GPA here: https://7sage.com/admissions/cas-gpa-calculator
We've rebuilt our admissions predictor from the ground up. The interface didn't change, but it uses a completely new algorithm, now trained on the most recent cycles. Expect lower but more accurate predictions.
What changed
- Newer data. It's now trained on the three most recent cycles, including 2025. The old version was learning from an era that was meaningfully less competitive than the one you're applying into.
- Stats are measured against current medians. Your GPA and LSAT are now evaluated relative to each school's medians rather than in absolute terms, so median drift is built in instead of ignored.
- Your numbers are treated as a package, not a checklist. The old model added up LSAT, GPA, and URM status as independent boosts. The new one learns how those factors interact with each other and with the tier of school you're applying to — the same LSAT can mean very different things depending on the rest of your profile and where you're applying.
- Fewer extreme predictions. The old model was happy to tell you 95% at a T14 on numbers alone. It shouldn't have, and the new one won't.
What that means for you
Most people will see lower numbers, and the drop will be largest at reach schools and for profiles that were previously getting very high admit odds. Nothing about your candidacy changed — the old figures were just too generous.
How we know it's better
Tested against actual 2025 outcomes, log loss (a standard measure that punishes confident wrong answers) fell from 1.35 to 0.85, and predicted probabilities now track observed results closely across the whole range. For scale: applicants the old model gave a ~90% admit chance were actually admitted roughly half the time. That gap is largely gone.
The usual caveat
It still only sees GPA, LSAT, and URM status. Essays, softs, work experience, letters, and school-specific priorities are invisible to it. Treat the output as a well-calibrated starting point for building a school list, not a verdict.
@smcat Correct. @NoNamed92 we're working on it, but no timeline. That's a more extensive change.
Now you can change any study day to a rest day or vice versa, so that as your plans change, your study schedule can change too.
Try it on your study plan today!
Feedback? Suggestions? Leave a comment!
@Phigginbo I didn't look for that—sorry. What I did see is that it's typical for students to do a learning phase followed by a practice phase in which they take about 1 PT a week with lots of review and drilling between each PT.
If you're feeling stuck or de-motivated, you're not alone. Improving your LSAT score takes a lot of practice.
How much? We ran the numbers: https://7sage.com/how-long-to-improve
@ChristopherTobin Feel free to leave feedback in this discussion as well. We welcome it!
If you just got your score back and you're wondering where to apply, head on over to our law school section and click "Build my school list" in the upper-right corner.
The feature isn't perfect yet, but it already builds on our admission consultants' expertise. Feedback is very welcome!
@elle114 Yes, but you can always change the schedule back to recover the past order.
We've upgraded the study plan! While you could always set your daily study hours, you can now customize how much you study each day of the week:
Head over to your study plan settings to pick the perfect schedule.
We're trying to improve our notes and WAJ system. Do you actually review your wrong-answer journal, or is the main value in taking the notes? If you review, how often?
Please tell us how you're using your notes and wrong answer journals, whether on 7Sage or another app!
We've been feverishly concocting better ways to study for years, but it was sort of like planting a tree. The roots (layout, look and feel, data structures, basic UX) took forever; no one noticed. Then came the trunk—the study plan, adaptive drills, better analytics—which people did notice, but also took for granted. (What's an LSAT study site without drills?)
Now it's bearing fruit.
We have a lot more in the pipeline. Stay tuned!
Earlier this year, we announced a $10,000 giveaway for people who tracked their law-school applications on 7Sage.
I’m happy to announce the winners:
AidanRusselAverbakh — $5,000
SiobhanRoy — $1,000
WonderfulWittySafety — $1,000
BenjaminWilson — $1,000
tylerv04 — $1,000
EmmaSodie — $1,000
Congratulations to all six, and thank you to everyone who tracked their applications.
Applying in the upcoming cycle? You can track your applications here. It’s free, keeps everything organized in one place, and helps future applicants understand how admissions cycles actually unfold.
Just in: Argument ER and Numbers Blitz. If you need a study break, go play and tell us what you think!
You can upload a new profile picture by clicking your robot and selecting "View public profile".
If you need a study break but just can't let the LSAT go, try our new learning games! They aren't a substitute for drills, but they can sharpen your intuitions and make the process of evaluating an argument more automatic.
Let us know what you think!
@sgdressel We're fixing it.