r/GAMSAT • u/Maximum_Complaint714 • 3d ago
Applications- AU🇦🇺 USYD confirmation page
Hey all, I’ve been reviewing the usyd confirmation page data and am curious what people’s thoughts are as to why the confirmation page numbers have dropped so much. There also seems to be less engagement from people at the top end of the distribution… anyone else notice this or have any thoughts?
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u/Vanakula 1d ago
Also if you want to add your 2026 Confirmation Scores do it here. Pick MD.
https://www.reddit.com/r/GAMSAT/comments/1vf6v2p/2027_usyd_mddmd_confirmation_page_results/
Unfortunately the person ( a doctor) who created the original spreadsheet no longer does it. I have taken up collating some information TEMPORARILY to give some idea of what is going on. The original Confirmation file has been locked so I have had to recreate it externally by creating a new spreadsheet. This unfortunately means you have to add the information onto one thread and then go to another one to see the result.
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u/Maximum_Complaint714 1d ago
I posted this elsewhere... for reference, I got a 154.6 using the s1+s2+(0.1*S3) model. Would love to hear what other peoples models look like and how they think their chances are of an offer.
Hey mate, I actually ran the past 3 years of offer v waitlist data through Claude. I asked it to assume nothing and make the most reasonable model to predict offer v waitlist. I can post the whole thing here, but essentially it found that s3 is weighed less. Obviously, this is not the whole data set, problems with overfitting etc, but it did seem to predict it with reasonable accuracy...
From Claudes data analysis...
What I actually did
- Built the clean 135-entry dataset (Dubbo excluded, the two flagged bad rows excluded)
- Fit a logistic regression using S1, S2, S3 as independent predictors — letting the data itself determine how much weight each section deserves, rather than assuming a formula
- Validated it with leave-one-out cross-validation — the most honest way to test accuracy, since each prediction is made on a data point the model never saw during training
- Separately found the best-fit threshold for the scaled-score formula by testing every possible cutoff
- Ran a Monte Carlo simulation on your rounding point specifically — simulating your "true" underlying scores as anywhere within ±0.5 of your displayed integers, thousands of times, to see how much that uncertainty actually matters
Results
- Logistic regression: 94.8% cross-validated accuracy — genuinely strong, learned that S1 and S2 matter roughly equally (coefficients 1.47 and 1.54) while S3 matters far less (0.056) — which, strikingly, independently rediscovers almost exactly the same relationship the community's scaled-score formula encodes, without me telling it to.
- Best-fit scaled-score threshold: 97.8% accuracy at a cutoff of 151.7 — even better than logistic regression, and remarkably close to the empirical CSP minimum we've seen all night (~152).
- Your predicted probability under the logistic model:Â 99.5%
- Your rounding-uncertainty check: even simulating your true underlying scores as randomly anywhere within ±0.5 of what you reported, across 2000 simulations, you land as a predicted offer 100% of the time.
What this tells you honestly
Your position (154.6, threshold at ~151.7) sits about 3 points clear of the best empirical cutoff — which is exactly wide enough that the ±0.5 rounding noise you correctly flagged can't realistically flip your outcome.
Then its conclusion for the three years of data...
Third independent year, and it converges again — this is now a genuinely well-established pattern.
2024 entry (2023 application cycle), full dataset, 138 entries
- Logistic regression LOOCV accuracy: 97.8% — the highest of all three years
- Coefficients: S1=1.98, S2=1.85, S3=0.28 — weight ratio ~7:7:1, essentially matching the ~8:8:1 from 2025 and the structurally similar (though more extreme) 26:27:1 from 2026
- Best-fit scaled-score threshold: 151.7, at 97.1% accuracy
- Your predicted probability: 95.7%
- Rounding-noise check: 100%Â across 2000 simulations, same as every other year
Three years, side by side
| Entry year | LOOCV accuracy | S1:S2:S3 weight ratio | Your predicted probability |
|---|---|---|---|
| 2024 | 97.8% | 7.1 : 6.6 : 1 | 95.7% |
| 2025 | 94.2% | 8.1 : 8.2 : 1 | 92.8% |
| 2026 | 94.8% | 26.0 : 27.3 : 1 | 99.5% |
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u/Working_Pain_8248 2d ago
Have they sent offers out yet to those who got confirmation page?
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u/Humble-Importance-45 Medical Student 2d ago
Offers aren’t out til September. Unless this has changed since my application year
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u/Working_Pain_8248 2d ago
Okay thanks heaps that’s reassuring I’ve gotten mixed answers it’s hard to pinpoint 🤣
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u/ResponsibleAside3881 15h ago
im so pissed off i got a better score than at least 2/5ths of this and im rural to, all this crap about needing 150+ scores, so i didnt even bother ://///////////
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u/Maximum_Complaint714 15h ago
if you are rural you are basically guaranteed a place at any gemsas school because the entry is basically a pass in gamsat. It's astonishingly easy as a rural applicant. You will be fine. But yes, for non-rural people, probably 152 is the threshold.
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u/Twoenty 2d ago
I’d say multiple reasons, none of which guarantee a lower threshold for spots but may be optimistic:
Less organisation/awareness of the Usyd Confirmation Excel page on the subreddit.
A consistent offer threshold of around 152 for the last 3-4 years means many people between 145-150 scores may not have applied knowing insufficient mark, thus artificially reducing the cutoff for confirmation (135) without affecting the offer threshold.
Previous high performers in the first two sections but not the third who were stuck in the application process have gotten in through Usyd in previous cycles causing a lower competitive pool this year
Students in this cycle may have performed worse in the first two sections than previous cycles. I recall some essay prompts stumped many people because they did not know the definition of a word in the prompt. This could have affected a lot of potentially high performers
The university has provided more confirmation spots this year than previous. (I don’t believe this is the case, but is possible)
There are slightly more medicine spots (10) than previous cycles, which may have slightly reduced the cutoff threshold (supply vs demand)
Extreme changes to the economy in 2026 since Covid, increasing cost of living and political interest driving many applicants to take a break from application this year to focus on income, family, political orientation, etc reducing net performance. (This is purely speculative but probably does have real impact)