Updated Post II Acceptance Rates 2023

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Hey all, I've been working on this community project for the last few weeks while I wait for the cycle to end.

You can see individual schools' updated application numbers, interviews, and acceptances that were in the 2021 sheet but now updated for 2023. This lets you see the application -> interview conversion rate and interview -> acceptance conversion rate. It also breaks stats down by in-state and out-of-state which is neat.

Soon I'll add all the school secondaries for the last 5 years and show cool info like the probability the secondary will show up in a future cycle based on the past trend. This should help with prioritizing pre-writing and make the whole admissions process less about Google searching and playing scavenger hunt for info.

Hope this helps a little with applying. I'll keep working on it out of boredom and see how it goes. If you have any feedback please let me know and I'll try to see what I can improve.

Link
 
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I just released the new application manager feature, where applicants can keep track of their cycle results (applications, interviews, acceptances, etc) all in one place. You can find it here.

Early next week, after a few thousand applications worth of data are filled in by applicants, I'll then release the corresponding live Cycle Results feature which anonymously aggregates the application statuses of users who opt-in and makes the results publicly visible. For example, you will be able to see that X anonymous applicant received a Y school interview on a certain date, then received an acceptance on a later date, etc.

I'm hoping that these features do a few things:

1) Helps applicants see when schools start sending out interviews, finish sending out interviews, pull from waitlists, make acceptances, etc in a very structured and organized way. The forums are great for finding this info but it requires users to look over dozens of pages to see individual thread replies to get this data. I figured having it all in one consolidated place on Admit would make it much easier to get this info.

2) Allows me to improve the school list builder by having access to thousands of data points on the individual admissions rubrics, weights, and point systems that schools use, especially when it comes to giving out interviews. The admissions process for giving out interviews is largely rubric-based, where screeners score applicants in several categories, then apply further modifiers to the applicant's overall score based on certain unique applicant metrics (undergrad ranking, SES and disadvantaged status, legacy, etc). If we ignore screener inconsistency and control for essay quality, identical applicants should consistently receive interviews to the same schools based on their primary application (this was also proven in the NYU ML admissions paper, where a scoring algorithm had the same predictive power as screeners in the admissions office for recommending applicants for interview, further review, or rejection.

It'll also be interesting to see how the points threshold needed to receive an interview at each school decreases over the course of the cycle, as well as learn about different screening tendencies. For example, 518 is a commonly shared MCAT soft screen for non-X factor applicants applying to Penn/Hopkins/NYU/WashU based on their admissions rubrics. We can also learn about other nuances, like the impact of low MCAT subsection scores, thresholds for minimum service hours at service-heavy schools, the influence of state residency (largely CA and TX) on OOS school admissions, etc.

My hope is that with enough data, the school list builder can become extremely accurate and help applicants reduce the size of their school lists and apply more efficiently to let's say 20 schools, rather than inefficiently to 30 or 40 schools. It also gives applicants the chance to focus on and submit higher-quality secondary essays rather than writing low-quality ones. With smaller applicant pools, schools can also spend more time holistically evaluating individual applicants with demonstrated mission fits, rather than waste hundreds of hours screening thousands of applicants. I think it would also be cool to one day be able to automatically suggest specific improvements to applicants' primaries, such as what activities or hours are missing from the primary that would increase the probability of receiving an interview at specific schools if incorporated. This is something for the future though that I'll probably work on closer to the start of the next cycle.

That's all for now and thanks for reading; I'm excited to see how this works out and will leave updates as I begin working on the updated version of the school list builder as well as other features 🙂

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HappyRabbit said:
I just released the new application manager feature, where applicants can keep track of their cycle results (applications, interviews, acceptances, etc) all in one place. You can find it here.

Early next week, after a few thousand applications worth of data are filled in by applicants, I'll then release the corresponding live Cycle Results feature which anonymously aggregates the application statuses of users who opt-in and makes the results publicly visible. For example, you will be able to see that X anonymous applicant received a Y school interview on a certain date, then received an acceptance on a later date, etc.

I'm hoping that these features do a few things:

1) Helps applicants see when schools start sending out interviews, finish sending out interviews, pull from waitlists, make acceptances, etc in a very structured and organized way. The forums are great for finding this info but it requires users to look over dozens of pages to see individual thread replies to get this data. I figured having it all in one consolidated place on Admit would make it much easier to get this info.

2) Allows me to improve the school list builder by having access to thousands of data points on the individual admissions rubrics, weights, and point systems that schools use, especially when it comes to giving out interviews. The admissions process for giving out interviews is largely rubric-based, where screeners score applicants in several categories, then apply further modifiers to the applicant's overall score based on certain unique applicant metrics (undergrad ranking, SES and disadvantaged status, legacy, etc). If we ignore screener inconsistency and control for essay quality, identical applicants should consistently receive interviews to the same schools based on their primary application (this was also proven in the NYU ML admissions paper, where a scoring algorithm had the same predictive power as screeners in the admissions office for recommending applicants for interview, further review, or rejection.

It'll also be interesting to see how the points threshold needed to receive an interview at each school decreases over the course of the cycle, as well as learn about different screening tendencies. For example, 518 is a commonly shared MCAT soft screen for non-X factor applicants applying to Penn/Hopkins/NYU/WashU based on their admissions rubrics. We can also learn about other nuances, like the impact of low MCAT subsection scores, thresholds for minimum service hours at service-heavy schools, the influence of state residency (largely CA and TX) on OOS school admissions, etc.

My hope is that with enough data, the school list builder can become extremely accurate and help applicants reduce the size of their school lists and apply more efficiently to let's say 20 schools, rather than inefficiently to 30 or 40 schools. It also gives applicants the chance to focus on and submit higher-quality secondary essays rather than writing low-quality ones. With smaller applicant pools, schools can also spend more time holistically evaluating individual applicants with demonstrated mission fits, rather than waste hundreds of hours screening thousands of applicants. I think it would also be cool to one day be able to automatically suggest specific improvements to applicants' primaries, such as what activities or hours are missing from the primary that would increase the probability of receiving an interview at specific schools if incorporated. This is something for the future though that I'll probably work on closer to the start of the next cycle.

That's all for now and thanks for reading; I'm excited to see how this works out and will leave updates as I begin working on the updated version of the school list builder as well as other features 🙂

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As usual, an invaluable service to applicants. One suggestion, though: when promoting the application manager, consider using an example applicant whose Admit Score is less than 750, so that it isn't quite so intimidating to those who aren't in the top 0.1%. 🙂
 
HappyRabbit said:
Sorry will see if I can do it today haha - been a bit busy on the new feature and getting ready for school
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Hey, just thought I would let you know that the dates are a little messed up in the Application Manager. On my end it looks like the Saturdays have no dates associated with them, compressing the week down to 6 days.
 

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In the last week, about 1,000 applicants have started using the Application Manager to manage the progress of their cycle, which is all used to crowd-source data for the cycle results feature I just released. Applicants can also click on other users' names in the live feed or within each school's data tables to see the progress of each other's cycles. For applicants who don't want their information visible in the cycle results, it can be disabled on the settings page.

You can find a link to the new feature here 🙂
 
Questions for you and @RunningMSN . You can carry this conversation as a group convo with me.

1) How do your programs compare regarding cycle behavior?

2) what is the average number of applications pet user? I also wanted to see if there is a sweet spot range for applications yielding IIs and offers, though more variables need to be considered? (Inspired by a conversation with advisors, and I realize you both may have insights...)

3) would you both be interested in a joint article about managing your anxiety while applying?
 
Mr.Smile12 said:
Questions for you and @RunningMSN . You can carry this conversation as a group convo with me.

1) How do your programs compare regarding cycle behavior?

2) what is the average number of applications pet user? I also wanted to see if there is a sweet spot range for applications yielding IIs and offers, though more variables need to be considered? (Inspired by a conversation with advisors, and I realize you both may have insights...)

3) would you both be interested in a joint article about managing your anxiety while applying?
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1) I don't have enough data yet on my side to give too much insight on this but I imagine it'll be very similar across both platforms. In terms of the feature itself, I spent a lot of time focusing on making the user experience as seamless as possible to make it easy for applicants to both track their own cycle as well as see aggregated data from other users. I think the idea of tracking cycles and learning more about how individual schools practice admissions is important to making the process more accessible. Making these free tools (Admit, CycleTrack, etc) is ridiculously difficult - it takes a lot of time, costs a ton of money, and there is usually no incentive for anyone to help applicants who can't afford to help the service cover costs. It makes sense that most of the resources that have been made so far are built in a Google doc/sheet by students, which is incredibly limited in reach (usually just gets passed around the forums). Instead of charging applicants to help keep the platform running and continue making more free tools available, one idea I've come up with is building software to help premed advisors in colleges provide feedback to and track the progress of students' profiles/applications, from freshman year to applying. I think that there's a huge disconnect between applicants who find the forums (or even just Reddit) and have the opportunity to learn about applying competitively, versus those whose only source of info is their school's premed advising office and some friends. Bridging that gap seems really important but I'll have to think more about how to do this exactly.

2) The average applicant is applying to 28.57 schools - it's important to note that the users on Admit (and I guess also on SDN) don't represent the average applicant pool. I was taking a look yesterday and the average Admit score is ~700 which is in the 95th+ percentile (something like 520/3.8 or so). One interesting thing I found is that there is a positive correlation between an applicant's score and the number of schools they apply to (applicants with higher scores are applying to more schools, whereas those with lower scores are applying to less). I thought it would be the complete opposite but there could be a few reasonable explanations for this trend.

3) Sounds awesome let's do it.
 
HappyRabbit said:
In the last week, about 1,000 applicants have started using the Application Manager to manage the progress of their cycle, which is all used to crowd-source data for the cycle results feature I just released. Applicants can also click on other users' names in the live feed or within each school's data tables to see the progress of each other's cycles. For applicants who don't want their information visible in the cycle results, it can be disabled on the settings page.

You can find a link to the new feature here 🙂
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Hi, HR. Will Dartmouth be added to the Cycle Results school list? It comes up on the Live Results column when I search for it, but that only lists the most recent user activity.
 
HappyRabbit said:
All of the schools should be there - is it not showing up for you?
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Seems like there's quite a few schools missing (as it hops around from 9 -> 13 -> 15 etc.) For me, it begins at the 9th ranked school.

Seems like the further you go, the less skipping there is, but there's significant skipping for the top schools

Update: #3 UPenn now showing up
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Also, I'd be very interested in adding 'secondary submitted' to the key statistics. I think it would help give context to schools that have a lot of applicants up front but don't follow through with secondaries (ex. Duke). I think seeing the results of how that correlates to the rate of interviews given would be really interesting.

Thank you so much for this tool @HappyRabbit It's such an amazing resource!!

(This is assuming secondary received means that the applicant has received a secondary, not that the school has received the secondary back)

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robot_soup said:
Seems like there's quite a few schools missing (as it hops around from 9 -> 13 -> 15 etc.) For me, it begins at the 9th ranked school.

Seems like the further you go, the less skipping there is, but there's significant skipping for the top schools

Update: #3 UPenn now showing up
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Yeah seems like there's a bug where schools randomly disappear - will fix thanks!
 
robot_soup said:
Also, I'd be very interested in adding 'secondary submitted' to the key statistics. I think it would help give context to schools that have a lot of applicants up front but don't follow through with secondaries (ex. Duke). I think seeing the results of how that correlates to the rate of interviews given would be really interesting.

Thank you so much for this tool @HappyRabbit It's such an amazing resource!!

(This is assuming secondary received means that the applicant has received a secondary, not that the school has received the secondary back)

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Will add!
 
this is an oddly specific request....wondering if on the cycle results tab, when you can sort by status under "all statuses" if there is a way to add a button that's like select all/select none? I like to see what schools have given out interviews but then you have manually unselect all the statuses you don't want which is mildly inconvenient (but not extremely in the slightest). thank you so much for your services and dedication <3
 
Hey there I have 3 quick things I think might be beneficial.

LECOM Bradenton and Nova DO are both missing from school choices

And I think pre interview hold would be a useful status as well 🙂
 
thank you for all your hard work! is ut san antonio (long) included? i can't seem to find it.
 
troy&abedintheAM said:
thank you for all your hard work! is ut san antonio (long) included? i can't seem to find it.
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I’m adding all the missing schools today (UT San Antonio, Orlando, etc), then will start working on the ability for future applicants to store their activities and track hours.
 
HappyRabbit said:
Hey all, I've been working on this community project for the last few weeks while I wait for the cycle to end.

You can see individual schools' updated application numbers, interviews, and acceptances that were in the 2021 sheet but now updated for 2023. This lets you see the application -> interview conversion rate and interview -> acceptance conversion rate. It also breaks stats down by in-state and out-of-state which is neat.

Soon I'll add all the school secondaries for the last 5 years and show cool info like the probability the secondary will show up in a future cycle based on the past trend. This should help with prioritizing pre-writing and make the whole admissions process less about Google searching and playing scavenger hunt for info.

Hope this helps a little with applying. I'll keep working on it out of boredom and see how it goes. If you have any feedback please let me know and I'll try to see what I can improve.

Link
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Have you decided how admit.org will handle the new (and pretty well useless) USNWR ranking system, when it is only inclusive of 50-60% of med schools? People still like to know the relative merits of schools, and climbing the highest mountain seems to be the American way. Just curious on your thoughts about this latest development.
 
RunnerDad said:
Have you decided how admit.org will handle the new (and pretty well useless) USNWR ranking system, when it is only inclusive of 50-60% of med schools? People still like to know the relative merits of schools, and climbing the highest mountain seems to be the American way. Just curious on your thoughts about this latest development.
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I'm working on a new ranking system that includes what I think are metrics that more accurately evaluate the quality of schools (including match quality, racial and socioeconomic diversity of class, financial aid provided to students, curriculum info like P/F or existence of AOA, home hospital for students to rotate at, etc). Will do a proper writeup with the methodology when it's done.

While I think that rankings do cause applicants to become overly neurotic, the removal of USNWR will simply cause people to look for a new list or way to compare schools - and I believe that there is incredible upside to the existence of ranks if it is done right and the metrics behind them support students.

For example, if we run with the assumption that schools will shape their curriculums and improve the school based on the criteria that go into the rankings, and rankings include criteria like financial aid given to students or a P/F curriculum, students become the end beneficiary of the rankings.
 
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Mr. Macrophage said:
Thanks on making such a useful site! I was wondering why Penn is listed as having internal ranking when their MSAR (and current students) says they don’t?
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When making the table I reached out to current students who said that they have an internal rank that is included in the MSPE letter. If you have more updated info you can send me a DM and I can look into it again, but from what I remember the Penn info was accurate. When I emailed the school for clarification they never replied, so you can imagine the challenge with making sure everything is 100% perfect.
 
HappyRabbit said:
I'm working on a new ranking system that includes what I think are metrics that more accurately evaluate the quality of schools (including match quality, racial and socioeconomic diversity of class, financial aid provided to students, curriculum info like P/F or existence of AOA, home hospital for students to rotate at, etc). Will do a proper writeup with the methodology when it's done.

While I think that rankings do cause applicants to become overly neurotic, the removal of USNWR will simply cause people to look for a new list or way to compare schools - and I believe that there is incredible upside to the existence of ranks if it is done right and the metrics behind them support students.

For example, if we run with the assumption that schools will shape their curriculums and improve the school based on the criteria that go into the rankings, and rankings include criteria like financial aid given to students or a P/F curriculum, students become the end beneficiary of the rankings.
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This seems very interesting. I do think that weighting financial aid/tuition reduction highly in the model does absolutely represent a strong indicator of school quality and competition.

P/F curricula are much more muddy; Penn is only one example of many schools that have internal rankings for pre-clinical, or qualitative grades on clinical (i.e., no grades reported, but coded descriptions given on the MSPE for cores). I don't think it's possible to accurately account for it in drawing comparisons, but it is a nice idea.

One factor often overlooked is the trajectories of alumni. I think match lists are one immediate indicator of this, but are subjective. I suppose you can collectively aggregate individuals matching in more competitive specialties, but the sample size is still very low and can be influenced by whether students wanted to match those specialties at all (which can be influenced by their school/environment) rather than an inability to match. I suppose you can instead take a specialty like internal medicine with a much larger sample size, and a wide range of competitiveness among institutions, and rank by aggregated sum/percentage of student body matching into top institutions. This is also influenced by student choice - but you have a higher power/effect size to minimize confounders.

For research rankings, I would also take into account alumni grants and manuscripts through Doximity data. Harder to get, but much better at actually defining a "research" ranking.
 
johnr42700 said:
This seems very interesting. I do think that weighting financial aid/tuition reduction highly in the model does absolutely represent a strong indicator of school quality and competition.

P/F curricula are much more muddy; Penn is only one example of many schools that have internal rankings for pre-clinical, or qualitative grades on clinical (i.e., no grades reported, but coded descriptions given on the MSPE for cores). I don't think it's possible to accurately account for it in drawing comparisons, but it is a nice idea.

One factor often overlooked is the trajectories of alumni. I think match lists are one immediate indicator of this, but are subjective. I suppose you can collectively aggregate individuals matching in more competitive specialties, but the sample size is still very low and can be influenced by whether students wanted to match those specialties at all (which can be influenced by their school/environment) rather than an inability to match. I suppose you can instead take a specialty like internal medicine with a much larger sample size, and a wide range of competitiveness among institutions, and rank by aggregated sum/percentage of student body matching into top institutions. This is also influenced by student choice - but you have a higher power/effect size to minimize confounders.

For research rankings, I would also take into account alumni grants and manuscripts through Doximity data. Harder to get, but much better at actually defining a "research" ranking.
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All very good points - for match list I planned on going with competitiveness of IM residencies since every school will have a bulk of students applying to IM and rankings of programs are fairly established. Here's some of the criteria that I've outlined so far which can be included:
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HappyRabbit said:
All very good points - for match list I planned on going with competitiveness of IM residencies since every school will have a bulk of students applying to IM and rankings of programs are fairly established. Here's some of the criteria that I've outlined so far which can be included:
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This looks great! A couple points:

1. Mean scores for Step 1 will be a little outdated, since it is now Pass/fail, but it may be possible to take the last year it was scored for the first "prototype" of the rank list. Longer term, it might just be better to weigh the Step 2 score higher in the model, and eliminate the step 1 score weight.

2. For mean indebtedness of graduates, I agree focusing on students who are at need is better. It may also be helpful to instead compare % of cost of attendance offered as FA between schools, as I am not sure how many lower-middle class students at schools that offer reduced/waved tuition (and/or a stipend for costs of living) are qualified for/taking out loans (i.e., some families support their kids financially for partial cost, even if they are of more modest means and that is a significant financial burden to them). However, this might require more leg-work to find out accurate estimates for full COA at each school.

3. I would consider the median stats of students, but lower than USNWR weights. These stats do not correlate with predicted physician performance, but do correlate with competition of admission, and board score performance - though the latter is already a measure you are including in the model. There are also schools that score significantly lower on other measures in the USNWR research ranking (in one case, by nearly 90% less federal research funding than similarly ranked schools this year), but ended up scoring high in recent rankings simply from stat-inflation. It's worthwhile to mention that these cases does not predict better alumni outcomes (i.e., matches) from schools.
 
I just finished up the new Admit medical school rankings after a few weeks of work and will share the list, methodology, and raw data tomorrow. I'm super happy with how it turned out 🙂

It generally aligns with the existing rankings but corrects a lot of the flaws that the US news methodology had like:

1) Not penalizing stat-heavy schools with low yields
2) Not ranking schools with lower MCAT medians and high % of low SES and URM matriculants properly (or vice versa)
3) Not including data outside of stats/research, like quality of home residency programs
 
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Full rankings are released and can be found here - most of the raw data incorporated is in this sheet.

The weights and criteria that went into the ranking are as follows:

Research Score - NIH Funding (23%)

I pulled all of the NIH funding dollars allocated to each medical school from here, which can also be found in the raw data sheet. Similar to the USNWR methodology, overall research funding makes up about ~65% of the research score. I decided to focus the research score entirely on NIH funding rather than other government funding, because I found it to be a more reliable indicator of the strength of research at a medical school.

Research Score - Research Dollars Per Faculty (12%)

The total number of faculty for each medical school was pulled from the AAMC here, which is also on the raw data sheet. NIH funding was divided by the number of faculty to produce a research dollars per capita figure. This helps control for smaller institutions that have a low number of faculty (and therefore a low overall funding value) but a high ratio per faculty member. USNWR also used this value, but also included the same metrics for government funding which I excluded since I found the NIH research funding to be more accurate indicator.

Stats Score - Median MCAT and GPA (35%)

The initial stats score was generated with a linear regression formula that takes in MCAT and GPA and returns an overall score. It is then adjusted to control for factors such as the percentage of matriculants that are URM and low SES %. This is important when looking at schools like UCSF, which have lower MCAT medians because they focus on accepting disadvantaged applicants (42% URM and 38% low SES), versus schools like NYU which have higher MCAT medians and an extremely low percentage of disadvantaged applicants (24% URM and 6% low SES).

It's also adjusted to incorporate the yield of each school. For example, while Vanderbilt has 521 MCAT median, only 28.19% of accepted applicants actually matriculate to the school (versus the average of 52% and range high of 71.8% at Harvard) and so their stats score should be punished proportionally.

Clinical Score - Strength of Home Residency Programs (30%)

The strength of the core rotation home residency programs at each medical school is used to create the clinical score. The five specialties used are Internal Medicine, Neurology, OBGYN, General Surgery, and Psychiatry. Points are assigned based on the strength and rank of each program (based on Doximity), and then summed across all medical schools after some modification to generate the clinical score.

Summary

I think that rankings have the potential to do a lot of good and motivate schools to pursue meaningful initiatives that improve the student experience. One of the issues I found with the USNWR methodology (which was only further reinforced after speaking to a current adcom) is that it forced schools to focus on the wrong goals - things like chasing high MCAT medians and low acceptance rates, rather than a diverse student body with unique experiences.

I intentionally didn't include acceptance rates as a criterion because it favors schools that try to field as many applications as possible rather than focusing on fielding applicants that match the school's mission (low number of secondary essays, no public screens, etc).

I'm most excited about the incorporation of URM %, low SES %, yield %, and the clinical score which I believe all contribute to a more balanced and accurate score that is hard to gamify or artificially inflate without actually making improvements to an institution. For example, a school that chooses to only accept applicants with high MCAT medians without assessing mission fit in an attempt to boost rankings will consequentially have lower yield percentages which negates the MCAT jump. Likewise, a school that builds a class with a large proportion of disadvantaged students won't be penalized for having lower MCAT medians.

As always, thank you to everyone for contributing to the development of these rankings and please leave your feedback if you have any below 🙂
 
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Chef'n Curry said:
This is awesome—thanks for compiling it! I'm curious as to what exact metric you used for NIH funding. Is it funding for the medical school itself? For the medical school plus its affiliate hospitals? Or something completely different?

I took a look at the source the NIH funding data was pulled from and thought I saw some discrepancies. For example, for UCSF, it seems like you're including funding for the medical school only, while for Harvard, the funding number seems to have something else added in.
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Harvard is made up of the affiliated hospitals (MGH/BCH/BW/DI) similar to how USNWR ranked it.
 
Awesome work as usual!!

I have a feature suggestion should you decide to implement it 🙂 It would be cool if the school statistics page also had the 'my schools' switch so applicants could compare the differences in number of applications, number of interviews etc. between all their schools on one page instead of fielding through all the schools for them.
 
robot_soup said:
Awesome work as usual!!

I have a feature suggestion should you decide to implement it 🙂 It would be cool if the school statistics page also had the 'my schools' switch so applicants could compare the differences in number of applications, number of interviews etc. between all their schools on one page instead of fielding through all the schools for them.
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Will add, thanks for the suggestion 🙂
 
Wish I had something like that when I was applying. You have a potentially million-dollar website on your hands.
 
It's been really cool to see how the Cycle Results feature can help learn more about the admissions process at each school. Take Mayo below for example - every interview sent out thus far has been to applicants with over a 522 MCAT (most at 523/524/525). Will be interesting to see how this changes as the cycle progresses and more data is contributed.


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HappyRabbit said:
It's been really cool to see how the Cycle Results feature can help learn more about the admissions process at each school. Take Mayo below for example - every interview sent out thus far has been to applicants with over a 522 MCAT (most at 523/524/525). Will be interesting to see how this changes as the cycle progresses and more data is contributed.


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I know that they have high admit scores but how can you deduce their MCAT scores from their admit scores? 🙂 That def provides some useful info as to how their admissions screening process may work!
 
@HappyRabbit Thank you so much for this site! It is amazing!

I have one question, and I am sorry if you have already answered this. What year are these acceptance data points from? I only ask because Quinnipiac seems to have 362 interviews but MSAR has them interviewing 490 last year. I am sure that changes the post ii acceptance so I just wanted to check!

You are awesome!
 
jacksparrow1 said:
@HappyRabbit Thank you so much for this site! It is amazing!

I have one question, and I am sorry if you have already answered this. What year are these acceptance data points from? I only ask because Quinnipiac seems to have 362 interviews but MSAR has them interviewing 490 last year. I am sure that changes the post ii acceptance so I just wanted to check!

You are awesome!
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They're from last year - what mainly matters is the percentages rather than the specific application or interview numbers, since they don't change much year to year.
 
Hi @HappyRabbit tysm for developing this website! I am wondering if the FIU post-II acceptance rate number is from USNWR as well? Thank you!
 
penguindoc2 said:
Hi! thanks so much for making this helpful site. I am unable to find Cleveland Clinic on admit.org, is it possible if you can add it? Also can you please add a "Hold" option on the application manager? thank you!!
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Cleveland Clinic is part of Case Western Reserve, and I don’t think separate stats are published even if they were considered separate schools.
 
HappyRabbit said:
They're from last year - what mainly matters is the percentages rather than the specific application or interview numbers, since they don't change much year to year.
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Thanks for this amazing resource! I was wondering if it would be possible to include more information with curricular attributes like internal ranking and grading systems? For instance, a numerical internal ranking is very different than a quartile internal ranking. Similarly, a H/HP/P/F system where a certain % of students get each category is different than a system where everyone can theoretically get an H.

Totally understand if this isn’t possible.
 
Was just looking over some of my schools- I think nova MD might be off- it says 1091 interviews and admits over 800 but MSAR has 345 interviews for class of 53.
 
Mr. Macrophage said:
Thanks for this amazing resource! I was wondering if it would be possible to include more information with curricular attributes like internal ranking and grading systems? For instance, a numerical internal ranking is very different than a quartile internal ranking. Similarly, a H/HP/P/F system where a certain % of students get each category is different than a system where everyone can theoretically get an H.

Totally understand if this isn’t possible.
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Unfortunately it’s not really feasible - I had quite a bit of trouble with reaching out to the schools and reading through the student handbooks as it is.

The main issue was that the information even coming from the schools itself was incorrect - in 30% of cases a school would reply saying that they were true pass/fail, had no internal rank, no MSPE adjectives, etc when I know it not to be the case. I get why this is done on the schools part but it makes building resources like this near impossible.

Maybe sometime in the future there can be a portal for schools to submit their information, but I’m not entirely sure and it still doesn’t address the above issue.
 
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