Village Super Market (VLGEA) Total Debt (2011 - 2026)
Village Super Market's Total Debt came in at $54.5 million for fiscal Q4 2026 (quarter ended Jul 25, 2026), down 6.9% from $58.53 million a year earlier and down 4.3% from the prior quarter.
Village Super Market (VLGEA) Total Debt (2011 - 2026) Analysis & Trends
Going back to fiscal Q4 2011, Village Super Market's Total Debt data covers 60 quarters.
- Total Debt has declined in each of the last three fiscal years, with a five-year compound annual growth rate of -6.0% (FY2021 to FY2026).
- Going back by fiscal year, Total Debt was $58.53 million in FY2025 (-19.8%), $73 million in FY2024 (-11.6%), $82.53 million in FY2023 (+10.2%) and $74.86 million in FY2022 (+0.6%).
- The fiscal Q4 2026 figure represents the lowest quarterly Total Debt since fiscal Q2 2020.
- Year-over-year, Total Debt has declined for 12 consecutive quarters, with an average decline of 13.7% over the last eight quarters.
- The fastest year-over-year change in Total Debt over five years came in fiscal Q1 2023 (growth of 14.1%), and the weakest in fiscal Q1 2026 (a decline of 20.4%).
- Business Quant data shows VLGEA's Total Debt at $56.94 million (Q3 2026), $59.36 million (Q2 2026) and $56.21 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 936.34 Bn | 892.78 Bn | 49.13 Bn | 50.41 Bn |
| 2 | Costco Wholesale | 443.48 Bn | 366.76 Bn | 12.19 Bn | 6.16 Bn |
| 3 | Sysco | 39.33 Bn | 33.58 Bn | 4.13 Bn | 13.52 Bn |
| 4 | Kroger | 38.87 Bn | 25.03 Bn | 7.86 Bn | 17.00 Bn |
| 5 | Dollar General | 29.16 Bn | 23.84 Bn | 3.68 Bn | 4.57 Bn |
| 6 | Caseys General Stores | 25.71 Bn | 23.71 Bn | 1.24 Bn | 2.43 Bn |
| 7 | Dollar Tree | 23.91 Bn | 20.53 Bn | 2.10 Bn | 2.93 Bn |
| 8 | US Foods Holding | 22.37 Bn | 22.17 Bn | 1.92 Bn | 5.41 Bn |
| 9 | Tractor Supply | 17.05 Bn | 16.22 Bn | 1.68 Bn | 2.15 Bn |
| 10 | Village Super Market | 626.63 Mn | 89.32 Mn | - | 54.75 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 25, 2026 | 54.75 Mn |
| Apr 25, 2026 | 56.94 Mn |
| Jan 24, 2026 | 59.36 Mn |
| Oct 25, 2025 | 56.21 Mn |
| Jul 26, 2025 | 58.94 Mn |
| Apr 26, 2025 | 60.88 Mn |
| Jan 25, 2025 | 63.19 Mn |
| Oct 26, 2024 | 70.62 Mn |
| Jul 27, 2024 | 73.91 Mn |
| Apr 27, 2024 | 75.38 Mn |
| Jan 27, 2024 | 77.78 Mn |
| Oct 28, 2023 | 80.16 Mn |
| Jul 29, 2023 | 84.22 Mn |
| Apr 29, 2023 | 84.92 Mn |
| Jan 28, 2023 | 87.72 Mn |
| Oct 29, 2022 | 82.88 Mn |
| Jul 30, 2022 | 76.83 Mn |
| Apr 30, 2022 | 76.31 Mn |
| Jan 29, 2022 | 78.22 Mn |
| Oct 30, 2021 | 72.65 Mn |
Village Super Market Total Debt 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=total-debt&ticker=VLGEA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-debt", "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=total-debt&ticker=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();