Village Super Market (VLGEA) Assets (2011 - 2026)
Village Super Market's Assets came in at $1.01 billion for fiscal Q3 2026 (quarter ended Apr 25, 2026), up 1.3% from $995.57 million a year earlier but down 1.8% from the prior quarter.
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Analysis
Village Super Market (VLGEA) Assets (2011 - 2026) Analysis & Trends
At the end of FY2025 (ended Jul 26, 2025), Village Super Market's Assets was $1 billion, up 2.2% from FY2024.
- Assets has increased in each of the last four fiscal years, with a five-year compound annual growth rate of 1.9% (FY2020 to FY2025).
- Going back by fiscal year, Assets was $981.66 million in FY2024 (+1.4%), $967.71 million in FY2023 (+4.7%), $924.45 million in FY2022 (+4.0%) and $889 million in FY2021 (-2.9%).
- The five-year range for quarterly Assets is $888.03 million (fiscal Q1 2022) to $1.03 billion (fiscal Q2 2026).
- Year-over-year, Assets has increased for 17 consecutive quarters, with growth averaging 2.0% over the last eight quarters.
- The fastest year-over-year change in Assets over five years came in fiscal Q1 2023 (growth of 7.1%), and the weakest in fiscal Q4 2021 (a decline of 2.9%).
- Business Quant data shows VLGEA's Assets at $1.03 billion (Q2 2026), $1 billion (Q1 2026) and $1 billion (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn | 293.91 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn | 86.43 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn | 28.40 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn | 49.49 Bn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn | 32.17 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn | 9.12 Bn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn | 14.03 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn | 14.34 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn | 12.16 Bn |
| 10 | Village Super Market | 655.09 Mn | 137.92 Mn | - | 1.01 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Apr 25, 2026 | 1.01 Bn |
| Jan 24, 2026 | 1.03 Bn |
| Oct 25, 2025 | 1.00 Bn |
| Jul 26, 2025 | 1.00 Bn |
| Apr 26, 2025 | 995.57 Mn |
| Jan 25, 2025 | 1.00 Bn |
| Oct 26, 2024 | 990.35 Mn |
| Jul 27, 2024 | 981.66 Mn |
| Apr 27, 2024 | 970.20 Mn |
| Jan 27, 2024 | 970.42 Mn |
| Oct 28, 2023 | 976.72 Mn |
| Jul 29, 2023 | 967.71 Mn |
| Apr 29, 2023 | 944.76 Mn |
| Jan 28, 2023 | 948.60 Mn |
| Oct 29, 2022 | 951.37 Mn |
| Jul 30, 2022 | 924.45 Mn |
| Apr 30, 2022 | 913.78 Mn |
| Jan 29, 2022 | 897.31 Mn |
| Oct 30, 2021 | 888.03 Mn |
| Jul 31, 2021 | 889.00 Mn |
API Access
Village Super Market Assets API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=assets&ticker=VLGEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "assets", "ticker": "VLGEA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=assets&ticker=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();