Village Super Market (VLGEA) Operating Leases (2019 - 2026)
Village Super Market (VLGEA) posted Operating Leases of $226.36 million for fiscal Q4 2026 (quarter ended Jul 25, 2026), down 6.2% from $241.22 million a year earlier but up 1.7% from the prior quarter.
Village Super Market (VLGEA) Operating Leases (2019 - 2026) Analysis & Trends
Since fiscal Q1 2020, Village Super Market has reported Operating Leases for 28 quarters.
- Annual Operating Leases has declined for four consecutive fiscal years, with a five-year compound annual growth rate of -4.0% (FY2021 to FY2026).
- In prior fiscal years, Village Super Market's Operating Leases was $241.22 million in FY2025 (-5.8%), $256.09 million in FY2024 (-4.0%), $266.68 million in FY2023 (-6.2%) and $284.3 million in FY2022 (+2.2%).
- Quarterly Operating Leases has run from a low of $222.65 million in fiscal Q3 2026 to a high of $284.3 million in fiscal Q4 2022 over five years.
- On a year-over-year basis, Operating Leases has declined in each of the last 14 quarters, with an average decline of 5.8% over the last eight quarters.
- The strongest year-over-year quarter for Operating Leases in the past five years was fiscal Q2 2023, with growth of 2.7%; the weakest was fiscal Q2 2026, with a decline of 9.7%.
- According to Business Quant data, Operating Leases for the three prior fiscal quarters was $222.65 million (Q3 2026), $229 million (Q2 2026) and $235.29 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Walmart | 961.60 Bn | 918.03 Bn | 49.13 Bn |
| 2 | Costco Wholesale | 451.41 Bn | 374.69 Bn | 12.19 Bn |
| 3 | Kroger | 41.07 Bn | 27.22 Bn | 7.86 Bn |
| 4 | Sysco | 40.11 Bn | 34.36 Bn | 4.13 Bn |
| 5 | Dollar General | 30.55 Bn | 25.23 Bn | 3.68 Bn |
| 6 | Caseys General Stores | 26.34 Bn | 24.34 Bn | 1.24 Bn |
| 7 | Dollar Tree | 24.96 Bn | 21.58 Bn | 2.10 Bn |
| 8 | US Foods Holding | 22.77 Bn | 22.57 Bn | 1.92 Bn |
| 9 | Tractor Supply | 18.16 Bn | 17.32 Bn | 1.68 Bn |
| 10 | Village Super Market | 654.29 Mn | 116.98 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jul 25, 2026 | 226.36 Mn |
| Apr 25, 2026 | 222.65 Mn |
| Jan 24, 2026 | 229.00 Mn |
| Oct 25, 2025 | 235.29 Mn |
| Jul 26, 2025 | 241.22 Mn |
| Apr 26, 2025 | 245.20 Mn |
| Jan 25, 2025 | 253.58 Mn |
| Oct 26, 2024 | 249.99 Mn |
| Jul 27, 2024 | 256.09 Mn |
| Apr 27, 2024 | 254.89 Mn |
| Jan 27, 2024 | 255.98 Mn |
| Oct 28, 2023 | 262.22 Mn |
| Jul 29, 2023 | 266.68 Mn |
| Apr 29, 2023 | 266.92 Mn |
| Jan 28, 2023 | 272.30 Mn |
| Oct 29, 2022 | 278.38 Mn |
| Jul 30, 2022 | 284.30 Mn |
| Apr 30, 2022 | 283.58 Mn |
| Jan 29, 2022 | 265.22 Mn |
| Oct 30, 2021 | 271.50 Mn |
Village Super Market Operating Leases 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=operating-leases&ticker=VLGEA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "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=operating-leases&ticker=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();