There have been several Heat Map tonics here recently. Many of them present counties colored to represent the number of teams in each.
Another way to present data on team density might use congressional districts rather than counties. It might be interesting to know which Representative represents the most teams, both by State and overall.
I donât have a bunch of data processing at hand, but looking through the teams that should be in my congressional district, I think there are about 65 teams in Michiganâs 1st congressional district - and I may be undercounting a bit, I have a list of active UP teams and then took the teams within 100 miles of Cheboygan which roughly corresponds to the district boundary, but a few might be near the southern edge I missed. And I tried to only count teams that are signed up for a 2024 event.
Iâm curious to know what other areas are like, but I suspect we may just have that combo of a large geographic area covered by one district and a lot of teams spread over that area, unlike a highly urban area where the district is small in area. And Michiganâs 517 teams spread over 13 districts gives an average of about 40 teams per district if evenly spread, so the 1st is at least above average.
Iâm going to boldly claim that either Michigan or Minnesota is likely to hold the top spot.
This is what happens when you have 4 feet of snow in mid October /s and your state is actually 2 different large landmasses and if you measure the state diagonally like you would a TV itâs 456 miles across. The population spread is wild and the further north you go the less dense it gets. Sadly one of the better engineering colleges is also way up there and they keep stealing our alums making it less likely theyâll drive all the way back to metro-detroit for kickoff. Glad theyâre in a good school though.
Would love the see the full congressional maps with a âdensityâ coloring as well for how many teams are in each. Might work on this. This idea makes me wonder how many teams are aware of their political districts and who they should be trying to schedule outreach time with for the most Impact.
There are problems with tracking teams by congressional districts.
For one thing, districts split counties, cities and townships. For example, youâd need to know what part of Detroit a team was in, what part of Macomb Township a team was in. Edit: Sometimes the location (address) for a team is not specific enough to know if thatâs were the team is physically located.
And they change every 10 years, sometimes more often if there are suits about boundaries being drawn out of compliance with various laws.
Agreed, doesnât seem like itâs the simplest task, but if you know the Geo coordinates for each zone and then convert the addresses teams have listed on TBA and convert those so you can see which zone they fall in. It wonât be perfect but it should be decently accurate. The hardest part is setting up the oddly shaped boundaries for each zone with each point in the shape being a geo coord as well.
I used to pretty regularly do congressional (and state legislative) level geocoding as part of a previous job. Itâs not easy, mostly for the reasons @GaryVoshol outlined.
Since congressional districts change boundaries over time and can have arbitrary boundaries, there is no foolproof mathematical way to do it (e.g. you canât match a list of postal codes to congressional districts, since neighborhoods can easily span multiple districts).
That said, the most accurate way to do this is to use an API which can take an address and look up congressional districts. As I explained in another post:
Some suggested using a teamâs main sponsor in hopes that it is a home high school or meeting place. However, a quick sample of a few teams shows that the first sponsor is only the meeting location roughly half the time, and Iâm not going to manually go through each team and find out where they meet.
So, the best I can do is some fuzzy results with the help of geocod.io, my favorite API for legislative district data.
A Very Fuzzy Congressional District Analysis
Data Disclaimers
Nearly all city/zip/state combos were geocoded with between 90% and 100% accuracy. A few of them geocoded at 75% accurate, but they all looked correct to me from a spot check.
THAT SAID - If a team does not have a zip code, that would put them at city center. For a city like Los Angeles, this could lead to being several congressional districts away. If a teamâs zip code spans multiple congressional districts (as is the case for many teams), they are placed at zip code center, which could be +/- one congressional district off.
ALSO - about 300 teams in the USA didnât geocode for whatever reason. In most of these cases, the lat/lng was found, but the API couldnât find a district. I think this can happen in scenarios where there are too many highly probable options for districts.
All that means, this data is a best guess, but really shouldnât be taken too seriously.
Teams are represented by roughly 414 out of the 435 House seats â a good, diverse representation!
48% of teams are represented by a Republican while 52% of teams are represented by a Democrat. This is fairly representative considering that the current makeup of the House is 51% R to 49% D.
Many of the top districts are in Michigan, predictably, with its high number of teams, relatively straightforward district boundaries, and concentrated popular areas. Coming in at 1 is the Honorable Representative Jack Bergman of Michiganâs 1st congressional district, representing a whopping (roughly, again) 68 teams!
Iâm not mapping these congressional districts. Maybe too much past trauma from previous jobs? But hereâs the data if someone wants to do something else with it:
Remember, there are 435 seats for the 50 states + one delegate each from DC, the virgin Islands, Guam, American Samoa, and the Northern Mariana Islands + a resident commissioner for Puerto Rico. So, the math is really 441-414 = 27 âseatsâ without teams, albeit a few of them with limited or no voting power.
Alabama 6
American Samoa At-large
California 22
California 35
California 41
Colorado 8
Florida 16
Florida 18
Florida 24
Guam At-large
Illinois 8
Kentucky 2
Mississippi 1
Montana 2
Nebraska 1
New York 9
New York 14
New York 22
Northern Mariana Islands At-large
Ohio 2
Pennsylvania 11
Puerto Rico At-large
Tennessee 5
Tennessee 6
Texas 1
Texas 11
Virgin Islands At-large
And, again, disclaimers from above that this might not be that accurate.
Looking through this thereâs not a single Michigan district without a team, and all of the districts have at least 23 teams it looks like⊠good stats and it means you likely have neighboring teams within a reasonable distance from you no matter where in the state you are
It gets real interesting if you map it out⊠I took a look at MN based on the districts, and geographically, districts 2,3,4,5,6 combined are smaller than any of the other 3. Add together the teams in 2-6, and you have more teams than any 2 of the others combined. It really gives you another way to look at team density.
Yeah, whatâs really interesting about congressional districts as opposed to other ways to slice and dice (county, postal code, city, etc.) is the apportionment process.
Warning - Redistricting 101 up aheadâŠ
For those unfamiliar, we start with 435 seats, give each of the 50 states one seat automatically, and are left with 385 seats. The remaining 385 seats are to be divided to the states proportionality based on the statesâ populations.
Where it gets really interesting, though, is within each state. Each state takes its number of congressional districts and is to divide their state into that number of districts, of as equal population size as practicable. Meaning, if a state gets 10 seats and has 8,000,000 people, each district should be comprised of as close to 800,000 residents as possible.
So, to @Jon_Stratisâ point, weâre now looking at data for areas which could be geographically unequal, but should, in theory be equal in population â within* each state. So, why is it that MNâs 7th congressional district has 41 teams while its 3rd congressional district has 15 teams, if theyâre roughly equal in population? The answer undoubtably includes geography â with the 7th district being way more spread out â but also lots of other socioeconomic and geopolitical factors. Thereâs no one-size-fits-all answer to this question, but it could make for a very interesting discussion on a state level (and maybe between states? see below note).
*The math should theoretically work out wherein each congressional district is the same population size between states, too, but practically speaking it isnât always the case. The math is State Seats = (Total Population / (435 - 50 ) X State Population and then within a state the math is District Size = State Population / Sate Seats. There are some problems, though, since 435 is a fixed number, districts are really hard to draw even for the best intentioned of folks, and there are folks with ulterior motives mixed up in the process.
0.8 M x 435 = 348 M, about 4% more than the latest figure I found by googling US Population.
And as you said, population of individual districts varies between measurements because Census data is updated once per decade, and then drawing new lines requires action, sometimes by people with conflicting agendas. Government of the people, by the people, for the people is a messy enterprise. However it beats the hell out of every alternative.