Village Super Market (VLGEA) Inventory (2011 - 2026)
Village Super Market (VLGEA) reported Inventory of $51.16 million for fiscal Q3 2026 (quarter ended Apr 25, 2026), unchanged from $51.18 million a year earlier and up 13.2% from the prior quarter.
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Analysis
Village Super Market (VLGEA) Inventory (2011 - 2026) Analysis & Trends
At the end of FY2025 (ended Jul 26, 2025), Village Super Market posted Inventory of $51.42 million, up 10.0% from FY2024.
- Inventory has increased for six consecutive fiscal years, with a five-year compound annual growth rate of 4.1% (FY2020 to FY2025).
- By fiscal year, Inventory came in at $46.74 million in FY2024 (+5.0%), $44.52 million in FY2023 (+0.7%), $44.19 million in FY2022 (+3.7%) and $42.63 million in FY2021 (+1.2%).
- Five-year quarterly Inventory spans a low of $42.63 million in fiscal Q4 2021 and a high of $54.15 million in fiscal Q1 2026.
- Year over year, Inventory gained in six of the last eight quarters, with growth averaging 4.6%.
- The high point for year-over-year Inventory in five years was fiscal Q1 2026 (growth of 10.9%); the low point was fiscal Q2 2026 (a decline of 9.4%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $45.18 million (Q2 2026), $54.15 million (Q1 2026) and $51.42 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn | 61.60 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn | 19.42 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn | - |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn | - |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn | 6.55 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn | 557.97 Mn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn | 2.45 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn | 1.70 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn | 3.52 Bn |
| 10 | Village Super Market | 655.09 Mn | 137.92 Mn | - | 51.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Apr 25, 2026 | 51.16 Mn |
| Jan 24, 2026 | 45.18 Mn |
| Oct 25, 2025 | 54.15 Mn |
| Jul 26, 2025 | 51.42 Mn |
| Apr 26, 2025 | 51.18 Mn |
| Jan 25, 2025 | 49.90 Mn |
| Oct 26, 2024 | 48.81 Mn |
| Jul 27, 2024 | 46.74 Mn |
| Apr 27, 2024 | 47.16 Mn |
| Jan 27, 2024 | 45.71 Mn |
| Oct 28, 2023 | 47.49 Mn |
| Jul 29, 2023 | 44.52 Mn |
| Apr 29, 2023 | 45.86 Mn |
| Jan 28, 2023 | 48.39 Mn |
| Oct 29, 2022 | 48.55 Mn |
| Jul 30, 2022 | 44.19 Mn |
| Apr 30, 2022 | 46.43 Mn |
| Jan 29, 2022 | 44.25 Mn |
| Oct 30, 2021 | 46.02 Mn |
| Jul 31, 2021 | 42.63 Mn |
API Access
Village Super Market Inventory 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=inventory&ticker=VLGEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "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=inventory&ticker=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();