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Allegheny County, PA — Gyms Saturation

How many gyms exist per person present — residents plus daytime workers — by ZIP code, compared with the U.S. average. Establishment data: Census ZBP 2023. Population: ACS 2024 5-year. 114 ZIP codes analyzed.

Includes: Gyms & fitness centers · CrossFit boxes · Boxing, martial arts & dance studios · Recreational sports centers. Counted together because official statistics use one 713940 code.

Measured density: Range spans bands — 1.06× the U.S. rate (between 1.06× and 1.95× once withheld ZIP cells are counted)

Why a range: Census does not publish a ZIP-by-industry count when that ZIP has 0–2 businesses. 87 ZIP cells in this county are withheld, 71 of them with residents. Each could hold 0, 1, or 2 businesses: counting them all as 0 gives the low end, counting them all as 2 gives the high end — the data cannot say where the truth sits. The density range uses only the populated cells, since ZIPs without residents are excluded from per-person rates. How ranges work

Range spans the U.S. rate   Allegheny County gyms — 106–195% of the U.S. rate

169 gyms are counted in Allegheny County — 1.1 per 10,000 people present (residents + daytime workers), 106% of the U.S. rate of 1.0.

On the comparable ZIP set (ZIPs with a published count in every year), the total has risen 20% between 2015 and 2023 (107 → 128). That set is smaller than today's county total. 2020–2021 were pandemic-distorted, and Census rounds counts, so small moves are within noise.

Measured supply density is highest in 15238 (Pittsburgh), 15228 (Pittsburgh), 15201 (Pittsburgh) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 15101 (Allison Park), 15108 (Coraopolis), 15241 (Pittsburgh).

BLS QCEW puts the latest county-wide count (2026 Q1) at 246 establishments, the freshest available signal.

Measured density: Allegheny County sits at 106% of the U.S. rate for gyms. 71 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 106% and 195% of the U.S. rate. Why. The highest measured density is in 15238 and 15228; the lowest measured density is in 15101 and 15108.

This is a supply-side read: it counts existing gyms and the people present, not foot traffic, income, rent, or whether locals want more. Treat low density as a question to check, not an answer.

Gyms
169–343
published count; upper bound counts each withheld ZIP cell as 2 (87 cells) (2023)
Per 10,000 present
1.1
residents + daytime workers
U.S. average
1.0
per 10,000 present
County index
1.06×
vs. U.S.
Latest quarter (QCEW)
246
2026 Q1 — county total
Residents
1,213,050
98 ZIPs with data
Workers
682,711
jobs located in county

Is the area growing?

Population
1,231,814
Census PEP, July 1 2024
Change since 2020
−1.4%
−17,857 people
Net migration 2024
+3,356
international +8,548, domestic −5,192
Jobs located here
712,047
LODES 2022, −2.4% since 2019

Allegheny County had an estimated 1,231,814 residents on July 1, 2024 — 1.4% fewer than in 2020 (−17,857). In the latest year it gained 1,676 people: births minus deaths −1,693, international migration +8,548, domestic migration −5,192. Components are published separately and may not sum exactly.

712,047 jobs were located in the county in 2022 (−2.4% since 2019), and 582,425 employed residents lived there (−3.9% since 2019). LODES counts wage and salary jobs covered by unemployment insurance plus federal jobs; it excludes the self-employed and military, and counts jobs rather than unique people. 2019→2022 spans the pandemic, so read it as one change, not a trend.

Population and migration say whether the customer base is growing. They do not say whether people want another business of this type. Definitions and limits →  ·  Full county detail →

ZIP gaining residents
2015–19 → 2020–24
Change
15205 Pittsburgh
+12.0%
15090 Wexford
+11.9%
15236 Pittsburgh
+9.6%
ZIP losing residents
2015–19 → 2020–24
Change
15233 Pittsburgh
−35.0%
15219 Pittsburgh
−31.2%
15132 Mckeesport
−10.6%

ACS 5-year estimates for 2015–2019 and 2020–2024. Only ZIPs with at least 2,000 residents in both windows and a change larger than the survey margin of error (90%) are listed — small ZIPs move a lot on paper without a real signal.

Nonemployer businesses

Not shown. NES 2024 does not publish fitness and recreational sports centers (NAICS 71394); only the broader recreation group (7139) is available.

Census Nonemployer Statistics 2024 (NAICS 2022). We do not approximate this figure.

Saturation map

Each ZIP area is shaded by its density of this business type per person present (residents + workers) vs. the U.S. average. Click any ZIP to zoom to its boundary, see its numbers, and switch to aerial imagery. Individual mapped shops appear as dots at street level — Show locations zooms you in to them (scroll or double-click to zoom).

Basemap:
Under 50% 50–100% 100–150% 150–250% 250%+ 0–2 (not published) / no data ZIP total (dot size) Mapped shop (OpenStreetMap, street level)

Map data © OpenStreetMap contributors, tiles by OpenFreeMap.

White dots are ZIP totals from the official Census count — the bigger the dot, the more gyms in that ZIP. They are aggregated, not individual shops. Turquoise dots are individual locations mapped in OpenStreetMap, shown only at street level; they are crowd-sourced and indicative, may be incomplete, and do not equal the official counts. Only the official ZIP totals feed the saturation index.

Market trend — up 20% since 2015

Number of gyms in Allegheny County across 2015–2023, on a consistent set of ZIP codes present in every year — so changes are real, not ZIP-boundary artifacts. 2015/2018 are pre-pandemic baselines; 2020/2021 are COVID-distorted.

107
2015
121
2018
133
2020
126
2021
129
2022
128
2023

Highest measured density

ZIP
vs. U.S. average
Index
15238 Pittsburgh
526%
15228 Pittsburgh
343%
15201 Pittsburgh
327%
15234 Pittsburgh
309%
15203 Pittsburgh
286%
15206 Pittsburgh
272%
15090 Wexford
270%
15205 Pittsburgh
264%
15017 Bridgeville
246%
15232 Pittsburgh
245%
15044 Gibsonia
221%
15237 Pittsburgh
209%
15146 Monroeville
199%
15220 Pittsburgh
184%
15143 Sewickley
182%

Lowest measured density

ZIP
vs. U.S. average
Index
15101 Allison Park
102%
15108 Coraopolis
105%
15241 Pittsburgh
110%
15122 West Mifflin
118%
15239 Pittsburgh
124%
15202 Pittsburgh
137%
15235 Pittsburgh
150%
15236 Pittsburgh
152%
15102 Bethel Park
169%
15143 Sewickley
182%
15220 Pittsburgh
184%
15146 Monroeville
199%
15237 Pittsburgh
209%
15044 Gibsonia
221%
15232 Pittsburgh
245%
Low measured density is not evidence of opportunity. A ZIP with few gyms may simply lack foot traffic, retail space, or demand. We rank only residential and mixed ZIPs here; employment hubs and visitor destinations are listed separately below. ZIPs where Census did not publish a count (0–2 businesses) are not ranked: they may be the least served of all, but the data cannot tell 0 from 1 or 2. Verify those locally.

Employment hubs & destinations

These ZIPs have far more workers (or visitors) than residents, so their counts are driven by daytime and visitor demand — not a place to read "shortage" from resident numbers alone.

ZIPNeighborhoodType ResidentsWorkersGymsIndex
15275Pittsburgh Destination 8614,032 4 549%
15222Pittsburgh Employment hub 5,72554,863 10 294%
15219Pittsburgh Employment hub 11,37635,729 3 100%
15056Leetsdale Employment hub 1,0412,242 0–2 —
15086Warrendale Destination 78810,407 0–2 —
15123West Mifflin Destination 272 0–2 —
15213Pittsburgh Employment hub 30,46661,917 0–2 —
15225Pittsburgh Employment hub 1,0852,887 0–2 —
15233Pittsburgh Employment hub 2,5966,678 0–2 —

Scroll the table sideways to see all columns.

All ZIP codes

Click a column header to sort. Index = gyms per 10,000 people present (residents + 0.5×workers) ÷ the U.S. average. 100% = exactly average.

ZIPNeighborhood ResidentsWorkersGyms Per 10kIndexStatus
15275Pittsburgh 8614,032 4 5.6 549% Very high density
15238Pittsburgh 12,86822,426 13 5.4 526% Very high density
15228Pittsburgh 18,2363,247 7 3.5 343% Very high density
15201Pittsburgh 13,3339,052 6 3.4 327% Very high density
15234Pittsburgh 14,0143,532 5 3.2 309% Very high density
15222Pittsburgh 5,72554,863 10 3.0 294% Very high density
15203Pittsburgh 10,37013,271 5 2.9 286% Very high density
15206Pittsburgh 29,05613,514 10 2.8 272% Very high density
15090Wexford 25,76313,495 9 2.8 270% Very high density
15205Pittsburgh 24,06025,757 10 2.7 264% Very high density
15017Bridgeville 17,78212,008 6 2.5 246% High density
15232Pittsburgh 11,3499,173 4 2.5 245% High density
15044Gibsonia 27,3707,035 7 2.3 221% High density
15237Pittsburgh 43,58824,830 12 2.1 209% High density
15146Monroeville 28,33221,714 8 2.0 199% High density
15220Pittsburgh 17,64417,527 5 1.9 184% High density
15143Sewickley 21,8519,684 5 1.9 182% High density
15102Bethel Park 30,3448,287 6 1.7 169% High density
15236Pittsburgh 31,31314,397 6 1.6 152% High density
15235Pittsburgh 33,9519,999 6 1.5 150% High density
15202Pittsburgh 19,5643,606 3 1.4 137% Above average
15239Pittsburgh 21,4104,456 3 1.3 124% Above average
15122West Mifflin 18,81611,920 3 1.2 118% Above average
15241Pittsburgh 22,2948,502 3 1.1 110% Above average
15108Coraopolis 42,79944,648 7 1.1 105% Above average
15101Allison Park 26,0365,012 3 1.1 102% Above average
15219Pittsburgh 11,37635,729 3 1.0 100% Below average
15006Bairdford 18054 0–2 — — Not published
15007Bakerstown 256314 0–2 — — Not published
15014Brackenridge 3,0951,239 0–2 — — Not published
15015Bradfordwoods 1,29164 0–2 — — Not published
15018Buena Vista 71299 0–2 — — Not published
15020Bunola 48181 0–2 — — Not published
15024Cheswick 9,3253,635 0–2 — — Not published
15025Clairton 16,9394,349 0–2 — — Not published
15030Creighton 1,018491 0–2 — — Not published
15031Cuddy 382403 0–2 — — Not published
15032Curtisville —9 0–2 — — Not published
15034Dravosburg 1,643455 0–2 — — Not published
15035East Mc Keesport 2,002248 0–2 — — Not published
15037Elizabeth 10,4171,813 0–2 — — Not published
15045Glassport 4,368615 0–2 — — Not published
15046Crescent 2,141508 0–2 — — Not published
15047Greenock 20317 0–2 — — Not published
15049Harwick 97418 0–2 — — Not published
15051Indianola 329387 0–2 — — Not published
15056Leetsdale 1,0412,242 0–2 — — Not published
15064Morgan 360183 0–2 — — Not published
15065Natrona Heights 10,8944,050 0–2 — — Not published
15071Oakdale 12,6633,697 0–2 — — Not published
15076Russellton 1,010208 0–2 — — Not published
15082Sturgeon 27518 0–2 — — Not published
15084Tarentum 9,7433,839 0–2 — — Not published
15086Warrendale 78810,407 0–2 — — Not published
15088West Elizabeth 344253 0–2 — — Not published
15091Wildwood —210 0–2 — — Not published
15096Warrendale —799 0–2 — — Not published
15104Braddock 8,0341,427 0–2 — — Not published
15106Carnegie 19,2447,724 0–2 — — Not published
15110Duquesne 5,1491,129 0–2 — — Not published
15112East Pittsburgh 3,655856 0–2 — — Not published
15116Glenshaw 14,4612,584 0–2 — — Not published
15120Homestead 18,0297,125 0–2 — — Not published
15123West Mifflin 272 0–2 — — Not published
15126Imperial 7,2763,386 0–2 — — Not published
15127Ingomar —121 0–2 — — Not published
15129South Park 10,789696 0–2 — — Not published
15131Mckeesport 8,2091,556 0–2 — — Not published
15132Mckeesport 18,8985,663 0–2 — — Not published
15133Mckeesport 6,112222 0–2 — — Not published
15134Mckeesport —65 0–2 — — Not published
15135Mckeesport 4,859505 0–2 — — Not published
15136Mc Kees Rocks 22,6237,187 0–2 — — Not published
15137North Versailles 10,0432,886 0–2 — — Not published
15139Oakmont 6,7023,252 0–2 — — Not published
15140Pitcairn 3,032395 0–2 — — Not published
15142Presto 1,513269 0–2 — — Not published
15144Springdale 3,771998 0–2 — — Not published
15145Turtle Creek 6,6951,843 0–2 — — Not published
15147Verona 15,7983,529 0–2 — — Not published
15148Wilmerding 2,351891 0–2 — — Not published
15204Pittsburgh 8,467868 0–2 — — Not published
15207Pittsburgh 10,9611,567 0–2 — — Not published
15208Pittsburgh 10,0942,159 0–2 — — Not published
15209Pittsburgh 12,3281,896 0–2 — — Not published
15210Pittsburgh 25,2271,776 0–2 — — Not published
15211Pittsburgh 10,7281,208 0–2 — — Not published
15212Pittsburgh 27,65233,203 0–2 — — Not published
15213Pittsburgh 30,46661,917 0–2 — — Not published
15214Pittsburgh 14,0481,077 0–2 — — Not published
15215Pittsburgh 11,9075,415 0–2 — — Not published
15216Pittsburgh 21,4713,797 0–2 — — Not published
15217Pittsburgh 25,7956,310 0–2 — — Not published
15218Pittsburgh 13,3793,354 0–2 — — Not published
15221Pittsburgh 29,3747,950 0–2 — — Not published
15223Pittsburgh 6,2552,511 0–2 — — Not published
15224Pittsburgh 10,6659,923 0–2 — — Not published
15225Pittsburgh 1,0852,887 0–2 — — Not published
15226Pittsburgh 13,9992,282 0–2 — — Not published
15227Pittsburgh 28,4604,199 0–2 — — Not published
15229Pittsburgh 15,1881,991 0–2 — — Not published
15230Pittsburgh —644 0–2 — — Not published
15231Pittsburgh —3,200 0–2 — — Not published
15233Pittsburgh 2,5966,678 0–2 — — Not published
15240Pittsburgh —3,149 0–2 — — Not published
15243Pittsburgh 13,4564,145 0–2 — — Not published
15250Pittsburgh —39 0–2 — — Not published
15258Pittsburgh —5,143 0–2 — — Not published
15259Pittsburgh —18 0–2 — — Not published
15260Pittsburgh 0758 0–2 — — Not published
15261Pittsburgh —261 0–2 — — Not published
15262Pittsburgh —2,010 0–2 — — Not published
15272Pittsburgh —2,574 0–2 — — Not published
15276Pittsburgh —3,445 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in Pittsburgh

The numbers above tell you how the market looks. To find a specific storefront, these marketplaces list available retail space for lease.

LoopNet
Largest commercial marketplace
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Crexi
Free listings + market data
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CityFeet
Retail space for lease
Browse Pittsburgh retail space →

Open vacancy data (actual empty units) is only published by some cities; where it exists we show it directly. Listings above are third-party.

Census withholds some ZIP-by-industry cells to protect small businesses. 0–2 means the cell was not published (Census publishes industry counts only at 3+ per ZIP), so the ZIP is left unranked rather than counted as zero. ~ means the count is estimated from the broader industry group and can be off by a business or two.

Follow Allegheny County and gyms

When a data vintage changes or a section of this report is revised, we post it to a public update feed. No email address, no account, no tracking — and nothing is sent unless something actually changed.

Subscribe to updates (RSS) How these numbers are built →

Methodology & sources

Establishments. U.S. Census ZIP Code Business Patterns (ZBP 2023), NAICS 713940 — fitness & recreational sports centers (gyms). Counts establishments with paid employees. ZBP is published annually with a ~2-year lag.

Fresh county signal. BLS QCEW (quarterly) is newer than ZBP — 2026 Q1 shows 246 establishments county-wide for this industry. It cannot be broken down by ZIP.

Population. U.S. Census American Community Survey 2024 5-year ZCTA population (table B01003). Workers are the ZIP's total employment from the same 2023 ZBP file.

Demand ("people present"). Demand comes from residents and daytime workers: residents + 0.5 × workers. This is the single documented assumption in the model and can be tuned.

Index. index = (ZIP establishments ÷ ZIP demand × 10,000) ÷ the U.S. average for this industry (1.03 per 10,000 present). It is a supply-side density measure; it does not capture income, rent, tourism, or whether locals actually want more.

Read the full methodology →  ·  Data sources & vintages →

BizGapMap — free, no-login small-business saturation reports for major U.S. counties. Built entirely from public U.S. Census, BLS, and IRS data (ZBP 2023, ACS 2024 5-year, PEP 2024, LODES, QCEW, IRS SOI). No forecasts, no revenue guesses — withheld cells are marked, and the few derived counts are labelled as estimates.