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February 7, 2017

Are There “Reverse-Splitter Friendly” Law Schools?

Are There "Reverse-Splitter Friendly" Law Schools?

We cover which law schools are “splitter-friendly” in this blog post. The analysis of the data in that post also gives us some insight into which school might also be “reverse-splitter friendly.” For the uninitiated, check out What Are Splitters, Reverse Splitters, and Super Splitters. It breaks down the differences to help you determine which one you are if any.

There are a couple things worth mentioning before we dive into that analysis, though. First, it may be true that splitter-friendliness is more of a “thing” than reverse-splitter friendliness and this certainly makes some sense. The non-cynical reason for believing law schools care about an applicant’s numbers has to do with what those numbers demonstrate regarding the applicant’s potential to be a successful law student and lawyer. The cynical reason, of course, is that schools game their USNWR rankings.

For my money, I think both reasons probably play a role. To a degree, schools care about numbers as a proxy for student quality. So, it makes some sense that they’d be more willing to accept low GPAs if the LSAT score is high than they would the reverse. This is simply because the LSAT provides a more even playing field. It allows for an apples-to-apples comparison among applicants. GPAs, on the other hand, can come from a variety of different majors and schools.  Evaluating one against another is a much trickier endeavor.

Another point: it’s tempting to think that a list of reverse-splitter friendly schools would simply be the negative image of a list of splitter-friendly schools, but this is not necessarily the case. It certainly could be the case that a school is friendly to both splitters and reverse-splitters, and is willing to dip lower on the GPA scale to snag high-LSAT candidates as well as dip low on the LSAT-scale to grab applicants with high GPAs. All I’m really trying to say here is that the concepts are not necessarily mutually exclusive.

How to Rank Schools

What I have done here is try to create an index number that incorporates information to answer our questions. The table below shows the index and the data used to compute it. I have to stress that because there is so little data available, and especially little data available on URM applicants, the following applies to non-URM applicants only. It is based entirely on non-URM applicant data. Unfortunately, I had to exclude URM data because it can really skew the overall picture. I also excluded any schools I did not feel that I had sufficient data-points for analysis.

Categories

  • LSAT Bump. A number from my own regression analysis, and indicates the % increase in the likelihood of admission for each additional LSAT point an applicant has.
  • GPA Bump. The GPA equivalent of the LSAT bump (the % increase for each .10 GPA).
  • LSAT/GPA Differential. To measure the relative importance of the two, we divide the LSAT Bump by the GPA Bump. The higher the number, the more relative weight the LSAT has.
  • Non-Splitter GPA.The average GPA of admitted non-splitter applicants.
  • Splitter GPA. The average GPA of admitted splitter applicants.
  • GPA Differential. Simply put, this is the difference between the previous two categories, and gives an indication of how much lower on GPA a school will go compared with its average in order to chase high LSAT scores.
  • Splitter Success. % of splitter applicants in the data who were accepted.
  • Non-Splitter Success. % of the non-splitter applicants in the data who were accepted.
  • Splitter vs. Non Success. This is Splitter Success divided by Non-Splitter Success, and gives us a measure of how splitters fare vs. their non-splitter counterparts. If a school admits splitters at a higher percentage than non-splitter, the number will be greater than 1 (and if the opposite is true, it will be less than one). The higher the number, the greater indication that the school is splitter-friendly.
  • Index. This is the number I devised to take into account the salient data from the other categories. It is simply (GPA Differential + LSAT/GPA Differential) * Splitter vs Non Success. The higher the number, the more splitter-friendly a school is.

Talking Numbers

The mean index number for the schools included is 2.31, so I set that as a benchmark, and then broke the schools down into five categories:

  • Very Reverse-Splitter Friendly: These schools have an index number that is more than two standard deviations above the mean. (Blue)
  • Reverse-Splitter Friendly: These schools have an index number that is between one and two standard deviations above mean. (Green)
  • Neutral-Friendly: These schools have an index number that is between the mean and one standard deviation above.
  • Neutral-Unfriendly: These schools have an index number that is between the mean and one standard deviation below.
  • Reverse-Splitter Unfriendly: These schools have an index number that is more than one standard deviation below the mean.

Indexing in Order of USNWR Ranking

As you can see, only one school — the University of Minnesota — is considered Very Reverse-Splitter Friendly under my analysis, with an additional 14 schools considered to be Reverse-Splitter Friendly. At the other extreme, Reverse-Splitter Unfriendliness is much more common than Very Reverse-Splitter Friendliness, with 12 schools falling into this category, and another 27 schools are in the Neutral-Unfriendly category. Remember, this is categorizing schools by their relationships to each other. Surprisingly, there’s more reverse-splitter friendliness than splitter-friendliness in the Top 14. Still, just as we can compare all the schools among themselves, we can isolate the Top 14 and do the same thing. So, how do they rank relative to each other?

For the Top 14, I kept the categories and color coding the same, but based everything off the mean index score of just the T14, which was 2.42 (ot all that different from the overall average, actually!). Here are the results:

Not much change at all, as you can see. The only real difference is that when we limit schools to the Top 14, Northwestern turns yellow to red. Perhaps the takeaway here is that splitters seem to be relatively more acceptance as you go down the USNWR ranks. For reverse-splitters, there’s not much difference between the top schools and lower-ranked schools. Although, of course, what “high LSAT” and “high GPA” means is obviously going to be different for Harvard than it is for Pepperdine.

As always, please keep in mind that this analysis is based on numbers taken from publicly available applicant-reported data (which I have cleaned to make as accurate as possible), and does not come from the law schools themselves. In other words, I wouldn’t look at any of the numbers in this table as perfect representations of reality, but it does make for interesting comparison and reflection, and hopefully is of some use to those pondering applying to law schools.

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Posted by PowerScore Test Prep / Law School Admissions / GPA, Law School Admissions, Law School Applications, LSAT Score 4 Comments

  • Norbert Sek
    February 07, 2017 at 4:45pm

    Thanks for the analysis. Do you have the equivalent for Canadian Law Schools ?

  • Dave Killoran
    February 07, 2017 at 5:10pm

    Hi Norbert,

    Thanks for the question! This was one of the very first questions we asked as well, and unfortunately there isn’t enough data on Canadian schools to craft a similar analysis. We’ll keep watching the data, and if anything changes we’ll post a splitter/reverse splitter analysis immediately, but for now we don’t have enough info to make a useful breakdown. Let’s hope that changes!

    Thanks!

  • Alex
    February 07, 2017 at 9:07pm

    Dave,

    Really interesting analysis, especially to me as I am a reverse-splitter and trying for some T-14s this cycle. Sorry if I missed this in the article but I am curious as to what the reverse-splitter GPA cutoffs are. For example, I see that the Chicago reverse-splitter LSAT score is 164.43. What then, would be the GPA of a person with a 164.43 GPA who has a success rate of 82.35%? I understand that the differential shows the relative weight of the GPA, but I am just curious about the GPA numbers. Thanks and again sorry if that statistics are going over my head, I wasn’t a stat major haha!

  • Alex
    February 07, 2017 at 9:36pm

    obviously meant 164.43 LSAT there instead of GPA my fault.

  • Dave Killoran
    February 12, 2017 at 12:52am

    Hey Alex,

    Sorry for the delay in a reply here, but I had to confer with Daniel, the author of the article, and he’s been unavailable for a little bit. However, I just received a reply from him a few minutes ago, and this is what he said: “This is a great question, and I have no idea why I didn’t address this in the articles themselves. Here’s the quick and dirty:

    To code an individual applicant as a reverse-splitter, that person had to have a GPA that was above the school’s 75th, and an LSAT below the school’s 25th (vice versa on splitters). So, any individual applicant could be a splitter for one school, but not for another…it all depends on the individual school’s LSAT/GPA numbers.

    So, when you’re talking about the average GPA of reverse-splitters who got into Chicago (with reverse-splitters getting in at an 85.35% rate), you’re talking about the average GPA of *all* the reverse-splitter admits to that school.

    I think that answers the question, but if not, let me know and I can clarify further.”

    Please let me know if that helps. Thanks!

  • Eric
    February 13, 2017 at 2:16am

    How is it that NYU, Georgetown, and UT have reverse splitter LSAT averages above the 25th percentile scores at each?

    Also, the first variable in your definition of “Index” is LSAT Differential, but I suspect you meant GPA Differential (numerical column 4). If so, how is the GPA Differential calculated (not defined above)?

  • Alex
    February 13, 2017 at 2:37pm

    Dave,

    Makes sense and that answers the question, thank you!

  • Dave Killoran
    February 13, 2017 at 7:55pm

    Hey Eric,

    Thanks for the question! We will look into this and post an answer as soon as we have it. Thanks!

  • Dave Killoran
    February 17, 2017 at 11:11pm

    Hey Eric,

    Thanks for the insightful comment! I spoke to Daniel about this, and you are indeed correct about the Differential. Here is his reply, and we’ve also made changes based on this exchange:

    “The commenter is correct: that column should be “LSAT Differential” and not “GPA Differential.” And the description for “LSAT Differential” should be “This is simply the difference between the previous two categories divided by 5 (so as to not give it too much weight as compared to the other variables), and gives an indication of how much lower on LSAT a school will go compared with its average in order to chase high GPAs scores.” So, that takes care of that (I was worried I had used the wrong numbers, but fortunately I had not!)

    As far as the reverse-splitter LSAT averages being above the 25th percentile scores at those schools, it is because the 25th percentile scores were different in each year. So, the average for NYU in the chart is 166.82, which is higher than the 25th for last cycle, but NYU’s historical 25th for the period covered is from 166-170 (as you know, schools had to kind of loosen up on the numbers over the past few cycles). Since that “average” number in the chart covers the past five years, that’s why it’s higher than this year’s 25th.

    Which brings up the question: how useful is that “average” number in the chart when the 25th percentile LSAT score has been a moving target for the past five years? What I can do (when I get time, which may not for several weeks) is calculate an “average” 25th for each school for the past five cycles. That way, you could look at the “average” LSAT of admitted reverse-splitters as compared to the “average” 25th percentile over that period. For example, NYU’s average LSAT score for reverse-splitter admits was 166.82, while the average LSAT 25th for the period covered was 168.25.”

    So, I think that covers it but if not just let us know!

  • Eric
    February 18, 2017 at 10:03am

    Thanks, Dave. That clarifies it. The proposed analysis does seem worthy because it’s ultimately important for the reverse splitter applicant to see whether they are above or below the most recent average LSAT of their high GPA peer set.

    I would also comment that the multiplier in the Index is based on reverse splitter vs non (i.e. everyone else). I’m sure it won’t materially change the conclusions since it’s ultimately a benchmarking exercise, but the more practical debate is usually reverse splitter vs splitter.

    Anyway, please convey my gratitude to Daniel for what is a very useful analysis.

  • Nick
    July 06, 2017 at 4:25pm

    Follow up question, Where do we find the average GPA of reverse splitters on the chart? If we go with the 75th quantile that would include both reverse and non reverse splitter. Also, if I understand the stats correctly, within the T14, U Chicago seems to be the best school choice for a high GPA (4.0) but low 160s LSAT? I scored a 162 on the LSAT but my PrepTest average was hovering closer to the high 160s and really low 170s on the June Exam; if possible that I am able to rescore my practice prep test scores again in September, how much would my lower LSAT score hurt in a ‘holistic’ LSAT review process? From my understanding, I won’t be seen as a reverse splittler but the much lower LSAT score still incurs a penalty for admission for the holistic LSAT review process since it is such a large difference?

  • Philip
    July 11, 2017 at 5:22pm

    Do you know why some school are more reverse splitter friendly than others like the intutition behind putting a greater weight on GPA/ more forgiving for a lower LSAT. Especially U Chicago seems really forgiving of a low LSAT score ( grateful for that). I heard Bolt is a high GPA school to but this chart shows it is not really that GPA heavy. I scored in the low 160s on the June LSAT with a 4.01 GPA (it is even higher when electives are removed) and I plan on retaking it in September 2017. I used to average 169 with a standard deviation of like 1 point; however, assuming I do not receive my PrepTest average of the high 160 (or even low 170s), and score say in the 166 range would my chances still be high for the T14 schools that are “green” on your post? Historically since the SAT (and even middle school standardized exams) I have underperformed relative to my GPA and my peers but back then the test score did not matter as much

  • Dave Killoran
    July 11, 2017 at 9:40pm

    Hi Philip,

    We can only see what the schools are doing from the data, not why they do it. As such, anything is speculative from that point. Of course, whatever it is is they are doing, it must relate in some way to what they most value and to experiences they’ve had in the past. It also is connected to the specific composition of the applicant pool each year, and thus changes can and do occur from season to season.

    With Boalt, they’ve always been known as a GPA school (and their multiplier always placed a higher value on GPA than other schools), but why they did that was particular to them.

    As for your chances (which I feel like I might have answered elsewhere possibly…?), your high GPA will certainly help and if you have a record of low test scores that will be a plus too. At that point, every single point on your LSAT score makes a difference. You’d still be in the discussion, but always with the LSAT every little bit helps.

    Please let me know if that helps. Thanks!

  • Dave Killoran
    July 11, 2017 at 11:51pm

    Hi Nick,

    I asked Daniel about this, and he said:

    “The short answer is that average GPAs are not found in the chart. I’m not sure exactly what the poster means in reference to the 75th quartile because for purposes of this analysis, those with a GPA above a school’s 75th but an LSAT below a school’s 25th are categorized as reverse-splitters, and this article is focused on that group specifically.”

    Perhaps you missed our other article on regular splitters: http://blog.powerscore.com/lsat/which-law-schools-are-splitter-friendly ?

    Thanks!

  • John
    September 18, 2017 at 8:31am

    Thanks for the great breakdown!
    I am still confused on what “Reverse Splitter Friendly LSAT” means on your analysis?

    Bolt is 161 whereas Chicago is 164. What does this mean in practice because this does not match up with the 25th Percentile LSAT scores of these schools either. Also, if this is the LSAT score we need (161 and 164) what GPA does this correlate too? I have a 3.99 LSAC GPA which clears Bolt’s 75% GPA by roughly 0.11 and Chicago’s by 0.05

  • Dave Killoran
    September 18, 2017 at 6:43pm

    Hi John,

    Thanks for the question! I don’t actually see that exact term used in the article, so I’m thinking you mean “Reverse Splitter LSAT?” If so, then it is “the average LSAT of admitted reverse-splitter applicants.” That’s a different number than the 25th percentile because it uses specific admissions data about splitters who were accepted, which is going to be a separate group than all attendees (splitter and non-splitter), which is where that 25th percentile is drawn from.

    I didn’t happen to write this article, so I can’t provide much more of a background on certain numbers like GPA aside from what is defined above, but those LSAt numbers don’t correlate to a specific GPA since they are average LSAT scores (as defined above). It’s looking at splitters and seeing who was admitted and then painting a very broad look at which schools are generally more or less splitter friendly. You can’t use it as an exact calculator, but, for example, if you had a 161, then the Boalt number matches up with the average of what they’ve accepted, which tells you that the 161 does not put you out of the running as long as you have a relatively high GPA. That same 161 is under Chicago’s average, and thus even with a high GPA you would know your chances are not as good as at Boalt.

    Thanks!

  • Ayse Gore
    February 04, 2018 at 4:51pm

    Hi Dave,

    Thank you so much for reading our comments!

    I am a lawyer in Turkey and graduated from number 1 ranked law school with 2.81 gpa. My gpa is pretty bad due to reasons like my dad is pretty religious and didnt allow me to follow lessons (because I am female). Although those obstacles I managed to finish law school in 4 years on time and I have 2 years work experience now.

    Do you think I have a chance to get accepted from top 25 schools? I wanted to get JD degree to practice law in New York.

    Thank you in advance.

  • Dave Killoran
    February 05, 2018 at 8:26pm

    Hi Ayse,

    Thanks for the question! A lot of your options will come down to your LSAT score. If you can do well there, then some doors will open up for you. Your GPA is also important, but you clearly have an explanation for that, and one that the committees would find compelling. You also have a demonstrated interest in and commitment to the legal system through your prior education. So, a lot of this will come down to your LSAT score. Do well there, and tell your story well, and you’d have a chance.

    Thanks and good luck!

Comments

  1. Jack Fleming says

    November 17, 2021 at 2:42 pm

    Hi Dave,

    Is there any chance that you all would consider updating this data to reflect the substantial increases in LSAT medians from this most recent (and highly volatile) admissions cycle? I’d be very interested to see how that might impact average LSAT scores for reverse splitter candidates. My sense would be that a reverse splitter applying to UC Berkeley these days would likely need a 165+ LSAT, considerably higher than the 161 average in the data above. Would love to get your take on this!

    Thanks,
    Jack

    Reply
    • PowerScore Test Prep says

      November 23, 2021 at 12:56 pm

      Hi Jack,

      Thanks for the post! We’re still in the process of tracking details through yet another unpredictable cycle, and we will wait to update until we have a clearer sense of how this year and last year fully play out. The last thing we want to do is publish an update prematurely that could mislead people. 🙂

      Thanks!

      Reply
  2. Grace Song says

    October 25, 2020 at 7:15 am

    Hello Powerscore, I was wondering if this data is still applicable, or if it’s considered outdated/inaccurate? Thank you! 🙂

    Reply
    • Dave Killoran says

      October 27, 2020 at 12:55 pm

      It’s still generally applicable! While it changes from cycle to cycle, this reflects general mindsets across schools 🙂

      Reply

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