An in-depth look at NYC-SIFT's Cutoff Estimates & Offer Prediction Bar

Every year, high school programs send out a fixed number of offers to fill seats for the following school year. Program applicants are placed on a ranked list and offers are sent to those applicants in order of rank. The point at which the worst ranked applicant was sent an offer is considered the “cutoff”.

For programs with “Open” or “Ed. Opt.” admission methods, lottery numbers weigh heavily in those rankings. The best lottery number starts with a “#00” and the worst starts with an “#FF”. This is a hexadecimal number that ranges from 0 to 255. Programs with a “Screened” admission method rank applicants by “group” (which is based on the average of their final 7th grade core course grades) and lottery number. This is slightly different from programs with a “Screened with assessment” admission method, which also takes into account a program-specific screening requirement, such as an essay.

NYC-SIFT only creates cutoff estimates & predictions for programs with “Open”, “Ed. Opt.”, or “Screened” admissions.

Open Programs

First, let’s consider “Open” programs. For these programs, an applicant’s lottery number is the only determining factor for ranking.

Currently, the DOE provides the number of applicants and seats available for each program. On average, programs send out offers that equal to about 150% of available seats. By default, NYC-SIFT assumes the lottery number distribution of the applicant pool is equal, meaning that there are just as many applicants with lottery numbers that start with “00” as they do with any other lottery number.

Open Program example

Using this information, let’s say we have an “Open” program that had 1,000 applicants and 100 seats. 150 offers are assumed to have been sent to the top 150 ranked applicants. The worst ranked applicant that was sent an offer should have a lottery number whose decimal value was 38 (150 / 1,000 * 255). Converting this number to a hexadecimal value would get you “#26”. This means the estimated cutoff for this program is a lottery number that started with “#26”.

We should expect a degree of error with this calculation due to the unknown distribution of lottery numbers and the fact that we are trying to use this information to predict the future. With this in mind, NYC-SIFT creates a lower and upper bound to the cutoff by subtracting and adding a hexadecimal value to the cutoff (equating to a 12.5% band). This means the estimated cutoff range will be displayed on NYC-SIFT as: “#16” to “#36”.

NYC-SIFT’s color-coded prediction band ranges from green to red. Internally, the color band is divided into 8 sections. Now imagine a line with 9 evenly spaced vertical markings, with mark 1 representing 0 and mark 9 representing 1,000 (the maxmimum number of applicants). Mark 4 would represent 22 (lower bound decimal value of hex value “#16”), mark 5 would represent 38 (the decimal value of the cutoff), and mark 6 would represent 56 (upper bound decimal value of hex value “#36”). Marks 2 and 3 would be equally spaced apart with values of 7 and 14, respectively. Marks 7 and 8 would also be equally spaced apart with values of 370 and 684, respectively.

Putting this all together, there is now a line with the following markings: 0, 7, 14, 22, 38, 56, 370, 684, and 1,000. On the color band, any value between 0 and 7 will point to dark green. Values between 7 and 14 will be green. Values between 14 and 22 will be light green. Values between 22 and 56 will be yellow. Values between 56 and 370 will be dark yellow. Values between 370 and 684 will be orange. Values between 684 and 1,000 will be red.

As you can see, we have now generated a graded colored ranking system for this program. Let’s say your lottery number starts with “#36” (which happens to be at the top of the estimated cutoff). Converting this into a decimal number gets us 54. Now we convert this number into our program rank, which is 211 (54 / 255 * 1,000). This would place us between marks 6 and 7, which is dark yellow. If your lottery number started with a “#05”, the converted program rank would be 19 (5 / 255 * 1,000), which is light green.

You’ll notice that that the conversions to color make it so that a very narrow set of applicants will get dark green, while the largest set of applicants will get yellow to dark yellow. This is intentional, as the system is doing its best to err on the side of caution. Any offer prediction value that lands you in dark yellow / light orange or better should be considered as a positive one. That being said, you may want to include at least one program where you are solid yellow or better for safety purposes.

Screened Programs

Screened programs differ in that applicants are placed into one of four groups based on 7th grade course grades. By default, NYC-SIFT assumes the group distribution of the applicant pool is equal, meaning that there are just as many applicants in Group 1 as they do with any other group.

Screened Program Example

Let’s say we have an “Screened” program that had 1,000 applicants and 100 seats. 150 offers are assumed to have been sent to the top 150 ranked applicants. With five screened groups (200 applicants per group), the worst ranked applicant that was sent an offer should be in Group 1 and have a lottery number whose decimal value was 191 (150 / 200 * 255). Converting this number to a hexadecimal value would get you “#BF”. This means the estimated cutoff for this program is a lottery number that started with “#BF”.

NYC-SIFT creates a lower and upper bound to the cutoff by subtracting and adding a hexadecimal value to the cutoff (equating to a 12.5% band within the group). This means the estimated cutoff range will be displayed on NYC-SIFT as: “(G1)#AF” to “(G1)#CF”. Since the applicant pool and offers are the same as the “Open Program Example”, the colored ranking system is also the same with the following markings: 0, 7, 14, 22, 38, 56, 370, 684, and 1,000.

The only difference now is including your screened program group as part of the conversion to the program rank.

Ed. Opt. Programs

Applicants are placed into one of three groups based on 7th grade course grades. Programs reserve 1/3 of all seats for each group. Since there are no factors other than lottery number that affect applicant ranking, calculations for “Ed. Opt.” programs are the same as “Open” programs.

Closing Remarks

There are also borough and DIA considerations that are used to calculate rankings, but I won’t be going into those details at this time. Hopefully this explanation was clear enough to shed some light on the inner workings of NYC-SIFT’s newest feature!

Hi! I have a question. Under “Offers” what does “P2” mean? I assume G1 G2 means Group 1 or Group 2. But what is P?

P means priority.

Some programs assign priorities to applicants. The most common are borough based (e.g. Brooklyn residents) and continuing students if it is a 6-12 school. The priorities should be listed as part of the program description.

In your example, offers are expected to go to priority 2 applicants.

That makes sense. Thank you so much! My older kid did this three years ago, without this information. This time around we are able to make much better choices because of this website.

Hi Adrian, Thank you for all of this - it is amazing. This is our 3rd time around applying to HS and what a gift these tools are! My question is about using the SIFT offer predictor tool for a kid who lives in Brooklyn but goes to school in Manhattan. Would you suggest I list his borough as Manhattan if I am looking at the 6 schools with boro priority? If I compare the doe tool to this one The DOE tool gives him 1 bar for El Ro but this tool gives him an arrow in the green zone. (He is SWD and Ran #79, Tier 1 and all that along with his school address in Manhattan is listed correctly in myschools). Im wondering about difference and if I am using the Sift tool incorrectly or if the DOE is not factoring in his boro priority… thank you!

Hi! You will need to switch your borough between Manhattan and Brooklyn in NYC-SIFT depending on what you are searching for. This is because you qualify for both Manhattan and Brooklyn priorities and there is currently no way to indicate multiple priorities in NYC-SIFT.

NYC-SIFT’s estimated cutoffs for SWD students with Manhattan priority for ElRo is Group 2 #46-#71, which means it thinks you will have a great chance of getting an offer. I don’t know why the DOE tool is giving you only one bar. I would expect it to at least give you two bars. According to Amelie’s data last year, SWD students were accepted up to Group 1 #A3, which means you would have received an offer even without borough priority. In addition, according to last year’s applicant data a Group 1 SWD student puts you in the top 3.3% of all SWD students, which should be another indicator that you have a high chance of getting an offer.

Hope that helps!

1 Like

Adrian, Can you please help me understand how to read this predictor? I thought I understood but maybe I’m wrong. P1 = means priority group 1 (which my kid fits into). But what does G3 mean - Tier/Group 3?
And if G3 means tier 3, why does the predictor say my kid is so far out of cut off range if they are above tier 3?
When I look at other schools the predictor makes sense with my kid’s info - just for this school it seems off.

You’re right. There’s something funny going on with either the estimated cutoff or the prediction bar.

I’ll let you know when I have it fixed!

OK, it should all be fixed now!

Q20K is one of a few programs that has different cutoffs for different priority groups so I had to rework how the system interpreted and displayed these cutoffs.

Let me know if you have any questions!

Thank you. Make sense. This website is a great resource.

Hi Adrian, What is assumed for the Manhattan 6? Are you assuming all 75% of Manhattan dedicated seats go to Manhattan students, and the remaining 25% go to a mix of the other boroughs, or are you assuming the schools won’t fill all 75% of seats with Manhattan applicants and therefore some from other boroughs may access them? I am trying to understand how conservative the predictor may be for my Tier 1/ good ran Brooklyn kid. It shows she has a good shot at several of these schools.

The way the calculations are done, there are no assumptions made. However, it just so happens that the remaining 25% do end up going to non-Manhattan applicants.

I’ll use Eleanor Roosevelt GE, non-DIA as an example:

  • The first calculation is to fill as many of the offers with Manhattan applicants. With 100 offers total, this means that the system will try to fill as many of the 75 offers with Manhattan applicants as possible. Last year about 42% of applicants were from Manhattan but I expect that number to be higher so the current calculation assumes that 52% will be from Manhattan. This means that of the 1,870 GE non-DIA applicants, 972 are assumed to be from Manhattan. All 75 offers will be filled by Manhattan applicants. Cutoffs will now be estimated for this first group (Manhattan applicants), which comes out to Group 1 #11 to Group 1 #2D.

  • The second calculation is needed to find the cutoffs for the remaining 25 offers. Now the entire pool is considered (remaining Manhattan applicants from the first calculation + all non-Manhattan applicants). So, 25 offers for 1,795 applicants. The estimated cutoffs comes out to Group 1 #06 to Group 1 #10. Manhattan applicants all the way up to Group 1 #2D were already sent offers, which means any remaining Manhattan applicants in this combined applicant pool must have worse numbers. Given that the cutoffs for this second calculation end around Group 1 #10, we know that all of these offers will be given to non-Manhattan applicants.

I believe this is the case for every one of the 6 programs. There are so many Manhattan applicants that the reserved 75% are always filled.

This second calculation is actually a lot more conservative than it needs to be. The proper way would be calculate the group and random number distribution for non-Manhattan applicants, add the remaining Manhattan applicants (whose distribution was calculated in step 1), then calculate the cutoffs. I decided not to do this because of the uncertainty around the size of the applicant pools for this admissions cycle. I have a feeling that the new unlimited application list size is going to throw a lot of numbers off, so it would be better to be a bit more conservative. That being said, I might not even be conservative enough!