Honestly it is a great scatterplot. They basically picked off the best and brightest, rejected the field. The two admits with low test scores and high GPAs probably had a bit of an angle and it worked. They saw through the other high GPA / low test score group. The others of course shouldn’t have even applied.
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Finance does have a significantly greater share of the US economy now than in past generations. Also, was it as heavily quantitative then compared to now?
The rising financialization of the U.S. economy harms workers and their families, threatening a strong recovery - Equitable Growth has the following image:
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They want to be able to predict yield accurately, so that they do not over or under enroll. However, that does not mean that they are trying to make their yield as high as possible.
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And just personally, I find it very implausible that colleges would be targeting higher yield percentages when almost no one even knows what they are.
Like, yield is not reported in US News. Yield is not even directly reported in the CDS. You actually have to make your own calculations to figure out any individual college’s yield.
And I actually do that sometimes. Because I have adopted studying college admissions as a hobby.
But what fraction of people in the real world are actually doing that? I think it is vanishingly small.
OK, so if you want to get conspiratorial, I’d at least focus on something people actually look at. Like, say, people sometimes actually look at things like enrolled student test score ranges. Theoretically, you might end up with better enrolled test score ranges by accepting more people with slightly lower test scores but much higher yield model projections, versus accepting more people with slightly higher test scores but much lower yield model projections, if that in practice pushes more enrollments to waitlist admits with even lower test scores.
That’s superficially plausible but actually fairly complex, because in theory if you could predict yield well enough in the aggregate, you could still get the class you want with just a sufficient number of low yield admits. And of course you can also try to manipulate yield with targeted merit, honors, and so on.
Which is actually what a lot of colleges do. Like Pitt, for example, has a reputation in my circles for not yield protecting, making it a popular Likely choice. And they do just admit a lot more people than they plan to enroll, and they have targeted merit and honors and so on, and apparently it all works out to their satisfaction.
OK, so then if a college is yield protecty, it probably is not because they care more about that statistic per se, since no one even sees it but rare people like me.
However, it might be because something about their situation makes it not possible to be like Pitt. Just to begin with, they might not have merit and honors. And then they also may find that year to year, their yield is not so predictable in the aggregate, or not with certain sorts of applicants. Like, if on average a large type of applicants yields at 3%, but sometimes it can be more like 2%, and sometimes 4%, that may seem like a small difference. But if you admit a bunch of these applicants on the assumption 3% will yield, those 2% or 4% years could really trip you up when that is multiplied out.
So to me the more plausible hypothesis is just that certain colleges get more of these low and hard to predict yield cases than others, and they don’t have much merit or honors or such to try to address that situation.
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There are dozens of us. Dozens!
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This looks a lot like a school I am very familiar and saw similar results with that is at the end of T20. They are very much an extreme on fit and will take lower stats over higher to achieve it.
And yet, UChicago will tout their very high yield numbers each year 
So, some schools do value high yield, and they seem to think the public does as well (but I agree with you that very few do).
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Yes, Chicago leapt to my mind as well.
I disagree that no one cares about yield. Some educated consumers do, and many schools do, and not only to hit enrollment targets. It is a way of assessing the desireability of a school. I am familiar with the inner workings of an extremely selective boarding school, and let me tell you, they are very focused on yield as a measure of desireability.
PS I think rating agencies also place importance on yield. This is no small thing.
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Agreed that yield is almost never discussed by the general public. But admit rate is obsessively reported by top schools (perhaps especially in those cases where they send out a press release announcing they will not be releasing their admit rate this year because the rate was just too low for such an announcement to be healthy.) And of course admit rates are tied to yield rates. If your model says a kid has only a 0.5% chance of yielding if admitted, why not turn his acceptance into a rejection instead?
So agreed that yield protection maybe isn’t the right name. I think “rejection protection” is better.
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This distribution also doesn’t surprise me much… at the tippy top lots of things matter…essays, major choice, etc. The officers know there isn’t a big difference between a 4.5 and 4.3 (and a 4.3 can be more impressive depending on course selection!)
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My kids’ school has used both Scoir and Naviance, and we’ve found the data to be unreliable as well. Because it’s a small school, it’s pretty easy to figure out scores, gpa etc. of some graduates we know well (just find the niche school they were accepted at and look at other schools & for some it’s easy to figure out if they were rejected, accepted, etc. bye-bye FERPA). Also I noticed for my son’s scores, his SAT never updated. First score showed up in the scatterplots and the table which was quite a bit lower than his final testing. Again, easy to figure out it was him as he applied to a bunch of unusual schools.
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Our school doesn’t release any information unless about 20 kids apply to that college in a year. So we have no information on any LACs, for example. My daughter wants to go to a LAC, so this is painful.
And yes…some of the data is off at our school too. Lots of waitlists and deferrals never get updated. Test scores are often not updated.
Garbage in and garbage out.
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One aspect to scattergram data that feels woefully missing is gender data. Our kids’ counselor made it very clear that our S25 and D25 could have different outcomes because of how much more competitive it is for girls. Being able to look at a school’s scattergram and filter the results for boys vs. girls would give significantly more signal to the data.
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No kidding. I have a D30 in addition to my S24. Already I was worried about how much could change in six years. But even holding that aside, I think it would be easy to overinterpret what happened with S24 in application to her.
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As the OP, I will point something out.
Above people have tried to guess what two colleges are associated with the two graphs. I have also gotten DMs from people trying to guess the colleges (and, again, I won’t be revealing the colleges).
Every single guess was wrong.
Every. Single. One.
And the CC parent crowd is probably the most admissions-astute group that you could ever find.
The two colleges in question both claim to practice holistic admissions. They both give very similar CDS answers on the dimensions of an application that are “important.”
Yet these two colleges have radically different admissions practices. At least for our high school.
And you can’t tell from the outside looking in.
“Holistic admissions” is a phrase that really means “we want to admit whomever we want, without fear of lawsuits.” To achieve this, critical information is withheld from consumers. And so students wind up shot-gunning applications in the hopes that their profile will align with the unknown admissions bias of a given school.
A sad state of affairs. At least for the T30 to T50. Admissions seems to get increasingly rational after that.
Just my opinion. Take it for what it is.
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I actually don’t find it that surprising.
The top students apply to the top colleges. Those colleges get so many excellent applicants that they are accepting and rejecting a lot of those students. I would venture to say that the GPA and test scores of those rejected are just about the same as those accepted. With an acceptance rate of around 6%, the rejected applicants to MIT would be plentiful and all have great stats.
If the schools were an Olympic committee recruiting runners for a relay team, yes, it would be a real head-scratcher as to why they didn’t take the four fastest runners. But they aren’t.
They aren’t just looking at GPA or rank, but what classes kids took. At our LPS, for example, there is only one Latin track, so no ability to pick up GPA increases for Honors. A kid who expresses an interest in classics and has A grades in Latin may have a lower GPA than the kid who took Spanish, which had differentiated tracks. But that kid could be very attractive to a school with a strong Classics program and faculty who want a strong cohort in their classroom.
Likewise, a non-native English speaker who has won international math competitions might not have great test scores but might be very exciting addition to a math program, yet this student’s test scores could be dragged down by their English score.
As others have noted, these tools have no way to call out athletes, legacies, or anything else.
This is all to say that anonymized data that shows only one attribute of what schools consider is only a very rough guide. Otoh, it’s a great conversation starter with your CC. If you ask “I see one student with a B+ average and a score of 1400 got in. Does this mean I have a chance?”, you may get an answer like “the gym is named after her family” or “She applied to their music program and had soloed with xyz Orchestra”.
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The plot tells us exactly who the “holistic” admits were (high GPA/low test score) vs. the non-holistic.
Also, don’t forget - many of the top schools don’t see themselves as marketing to customers but as custodians of a brand and carriers of a societal mission.
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Yes because a scattergram allows you to identify the gifted cellist, the writer who just got a YA novel published and is under contract for an as yet unwritten manuscript, the self-taught linguist who speaks five languages and is now teaching herself Korean and hopes to work in National Security some day, etc. You must be very talented to suss these things out of a single snapshot!
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The scattergrams for selective schools at my daughter’s HS were basically useless for predicting admission.
As noted above, there is so much missing from the scattergrams, including intended major. Even at schools who say they don’t admit by major/division - How many CS hopefuls are they really going to take from the same school?
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