My kids have also graduated from college, but when I went to the site, it looks like there is still a chance feature.
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I donât doubt that they are retroactively fairly accurate in aggregate. Itâs not difficult to back-test data.
But the fact that they âupdatedâ the chances several months ago, likely with last yearâs data, and numbers changed by a meaningful amount, tells me that past performance is only a moderately correlated indicator of future results.
It also gives aggregate data - you canât be 25% accepted to a school. Itâs probably one of the better/best historical statistical analysis tools, but be sure to use it for what it is.
Our Naviance scatterplots show no students ever accepted to schools that my daughtersâ friends are currently attending, so I donât hold it to be any more accurate. My daughter has never been shown as any status at the school she attended, even though her âschool attendingâ is correct and her GPA/scores are shown.
To add to all of the above, the most recent Common Data Set data is prior to most schools being test optional. I think predicting is much more challenging in the test optional environment, especially with only one year of data to go on, if CV was even to seek that data out.
For targets and âsafetiesâ (using that term loosely), I donât believe thereâs any way to account for demonstrated interest.
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Iâll bite. Certainly, the College Vine site has flaws, one big one being a lack of rigor assessment(just asks #AP and #honors). Howeverâfor fun I put in D21 (used the full EC descriptions and the whole bit)âIt had every single school she applied to in the correct âbinâ such as match and reach and hard target(our school calls that high match/low reach) and gave a similar % chance that her GC gave her for each school ( harsher than our naviance âchancerâ which is horrible and called half the ivies âmatchesâ ) . Her success was predicted very accurately by CollegeVine just as it was by her GC (accepted to safeties and all the matches , in to one higher match"hard target" and one reach, denied only at other reaches). One flaw is State schools do not seem to change based on residencyâI played around with it and in-state gave only a small boost and was still much lower than our HS naviance results reveal.
So as long as it is âjust for funâ, whatâs the harm? It seems to be more accurate than most with my limited anecdotal experience.
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2devils I had the same experience and I have to say I was rather impressed. Maybe CDS data has a lag, and rigor only estimated by APs and Hs. And of course essays and reccs cannot be used as inputsâŠ
But I have to say, it was surprisingly useful for comparing possibilities⊠but not predicting them. It ranked ours more or less in the right order and groupings as GC.
Itâs one tool and a pretty good one at that. Ignoring the predictor, the data for the schools in one place was valuable- especially given its (although lagged) accuracy.
Iâd give it a shot if you havenât.
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Like any other statistical tool- it is going to do a better job with big universities than small colleges. Figuring out that a kid has a 75% chance of getting into U Michigan is not that hard; figuring out if that same kid is likely to get into Amherst is a lot harder. Bigger pool, more datapoints, less ânoiseâ at Michigan given the size of its freshman class.
If youâre having fun collecting data and making spreadsheets, more power to you. In my experience, a better use of time is finding a couple of ârock solid safetiesâ which are affordable, where a kid is almost certain to be admitted based on the very well publicized stats, rather than investing time in trying to predict/game/compare.
Does it help to know that a kid has a marginally greater chance of being admitted to Cornell engineering than MIT? Does it help to know that a kid has almost twice the probability of being accepted to U Penn (two parents are legacies, kid has applied early) vs. Princeton if you are comparing 14% to 7%?
But as hobbies go- seems like more fun than pickleball so have at it!
Yes, it certainly depends on what youâre looking for. All of D22s schools are in the same âbucketsâ I have, and while the percentages may seem a bit off, I donât think they are meaningfully so.
Assigning a specific number is actually a bit silly. They may have been better off with just the classifications, maybe adding a few to be slightly more granular.
But I realize an exact number makes them seem âpreciseâ or âaccurateâ to many.
(And yes, 2021-22 CDS are going to be a fiasco, as already seen in website-published data)
Itâs available data on CDS, but showing differences in admit rates by gender (useful to STEM girls at some schools where admit rate is 2x) is very handy.
Not in CDS, so I would be curious how they source, differences between overall admit rates/stats and those experienced by people in your race/ethnicity. I know this is the third rail of admissions and hate to mention it, but if schools have differences, this is important to URMâs.
I just did this for fun. D went test optional so I didnât put scores. I did a fairly thorough job of listing her ECs. The calculator said one of her schools was reaches (Davidson) with 15% acceptance rate for her. She got in. Colgate, Lehigh, Richmond, and BC all hard targets in the upper 20%s for her acceptance rate. She got into all. I didnât bother with her safer schools.
I donât know what this means or what it tells anyone. The overall acceptance rate column was pretty close to her specific acceptance rates.
Edited to add: Added Vanderbilt. Her acceptance rate was 8%. Overall is supposedly 10%. She was denied.
Iâd be curious if anyoneâs personal acceptance rate is way different than the overall one for any school.
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How did College Vine do compared to your daughterâs schoolâs Naviance ?
Which was more accurate ?
Not nearly as good as Naviance. I felt very good about her chances at all of the schools where she was accepted. Felt like she had closer to a 80-85% chance at Davidson, BC, Lehigh, Colgate, and Richmond. No one from our school was denied at those schools with her GPA and rigor but, without sending scores, we couldnât feel completely secure.
Hard to say for Vandy. According to Naviance, it looked like she would have gotten waitlisted in RD but I think not sending a score there hurt.
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I found Naviance to be wildly off. Very unreliable. I wouldnât use it for anything but managing the recommendation process. It isnât useful for anything else.
College vine prediction probabilities might be suspect, but ranked odds of schools accurately. I would not count on their 22% chance of being admitted to school A. But I it did value their estimation that my D had a better chance at school A than school B.
That said, even their probabilities were not terrible.
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But admittedly I donât have admissions decisions in hand. I am comparing CV to what odds out GC provided and they were pretty close.
We have to be careful about what function we are talking about in Naviance. My guess is @homerdog used the scattergrams, not the college search/match function to help categorize schools.
Not all schools activate the college search function, and as we know not all schools populate the scattergram data accurately and/or completely.
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Sorry for not being more clear. Yes, we used the scattergrams on Naviance.
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Good point! the naviance College search chancing was the one that I meant as way off, listing Vandy and some ivies as âmatchâ schools, while the scattergram clearly indicated they were reaches. GC gave V as 15% chance, CollegeVine gave her a 20% chance(âReachâ on CV is less than 25% I believe), overall CV is 10%, overall acceptance rate at our HS to V is 22% before this yearâŠShe was denied. Only one of 11 was admitted so the historical HS data was no help. 2021 was a weird year and it will be interesting to see how Naviance & C-Vine look when D23 is ready.
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I just looked - Naviance had my D23 as a âmatchâ with Stanford, Harvard, Princeton, Yale. On CV these as âReachesâ, with 17-20% likelihood of admittance. You can argue these percentages, but CV clearly and accurately does not deem them a âmatchâ.
CV might not be spot on- its impossible to quantify certain things. But in order or magnitude, it appears much better than whatever algorithm Naviance uses. I feel badly for anyone who uses Naviance for this and gets their hopes up and then crushed.
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Good to know, but surely the Naviance scattergrams would show those schools as reaches, no?
Indeed- the scattergrams most surely would. If the data sets provided by GCâs were more robust, they would be much more useful.
Iâm somewhat surprised that Naviance shows any Ivy type school as a match for any student knowing what we all know.
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