Village Super Market (VLGEA) Total Debt (2011 - 2026)
Village Super Market's Total Debt came in at $56.94 million for fiscal Q3 2026 (quarter ended Apr 25, 2026), down 6.5% from $60.88 million a year earlier and down 4.1% from the prior quarter.
Village Super Market (VLGEA) Total Debt (2011 - 2026) Analysis & Trends
At the end of FY2025 (ended Jul 26, 2025), Village Super Market's Total Debt was $58.53 million, down 19.8% from FY2024.
- Total Debt carries a five-year compound annual growth rate of -6.3% (FY2020 to FY2025).
- Going back by fiscal year, Total Debt was $73 million in FY2024 (-11.6%), $82.53 million in FY2023 (+10.2%), $74.86 million in FY2022 (+0.6%) and $74.44 million in FY2021 (-8.0%).
- The five-year range for quarterly Total Debt is $56.21 million (fiscal Q1 2026) to $87.72 million (fiscal Q2 2023).
- Year-over-year, Total Debt has declined for 11 consecutive quarters, with an average decline of 14.3% 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 $59.36 million (Q2 2026), $56.21 million (Q1 2026) and $58.53 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn | 50.41 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn | 5.67 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn | 13.52 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn | 17.00 Bn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn | 4.57 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn | 2.43 Bn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn | 2.93 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn | 5.41 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn | 2.15 Bn |
| 10 | Village Super Market | 655.09 Mn | 137.92 Mn | - | 56.94 Mn |
Historic Data
| Date | Value |
|---|---|
| Apr 25, 2026 | 56.94 Mn |
| Jan 24, 2026 | 59.36 Mn |
| Oct 25, 2025 | 56.21 Mn |
| Jul 26, 2025 | 58.53 Mn |
| Apr 26, 2025 | 60.88 Mn |
| Jan 25, 2025 | 63.19 Mn |
| Oct 26, 2024 | 70.62 Mn |
| Jul 27, 2024 | 73.00 Mn |
| Apr 27, 2024 | 75.38 Mn |
| Jan 27, 2024 | 77.78 Mn |
| Oct 28, 2023 | 80.16 Mn |
| Jul 29, 2023 | 82.53 Mn |
| Apr 29, 2023 | 84.92 Mn |
| Jan 28, 2023 | 87.72 Mn |
| Oct 29, 2022 | 82.88 Mn |
| Jul 30, 2022 | 74.86 Mn |
| Apr 30, 2022 | 76.31 Mn |
| Jan 29, 2022 | 78.22 Mn |
| Oct 30, 2021 | 72.65 Mn |
| Jul 31, 2021 | 74.44 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();