Weis Markets (WMK) EBITDA (2010 - 2026)
Weis Markets (WMK) recorded EBITDA of $61.16 million in Q2 2026, up 0.5% from $60.83 million a year earlier but down 8.9% from the prior quarter.
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Analysis
Weis Markets (WMK) EBITDA (2010 - 2026) Analysis & Trends
On a TTM basis, Weis Markets' EBITDA came in at $254.53 million as of Jun 27, 2026, up 6.3% year-over-year; for FY2025, it came in at $238.44 million, down 0.8% from FY2024.
- Annual EBITDA has declined for three straight years, with a five-year compound annual growth rate of -1.9% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $240.26 million in FY2024 (-0.5%), $241.58 million in FY2023 (-7.5%), $261.08 million in FY2022 (+4.6%) and $249.52 million in FY2021 (-5.0%).
- Quarterly EBITDA has ranged from $51.4 million in Q1 2025 to $74.29 million in Q2 2022 over the past five years.
- On a year-over-year basis, EBITDA has increased for three consecutive quarters, with growth averaging 7.7% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 36.1% in Q4 2024, against a decline of 18.9% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $67.16 million (Q1 2026), $73.91 million (Q4 2025) and $52.31 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 862.64 Bn | 825.34 Bn | 49.13 Bn | 13.31 Bn |
| 2 | Costco Wholesale | 409.33 Bn | 338.62 Bn | 9.01 Bn | 3.41 Bn |
| 3 | Sysco | 37.65 Bn | 31.90 Bn | 4.13 Bn | 1.24 Bn |
| 4 | Kroger | 35.26 Bn | 21.42 Bn | 7.86 Bn | 1.71 Bn |
| 5 | Dollar General | 27.43 Bn | 22.11 Bn | 3.68 Bn | 1.05 Bn |
| 6 | Caseys General Stores | 22.41 Bn | 20.40 Bn | 1.24 Bn | 601.08 Mn |
| 7 | Dollar Tree | 21.77 Bn | 18.40 Bn | 2.10 Bn | 869.90 Mn |
| 8 | US Foods Holding | 20.27 Bn | 20.06 Bn | 1.92 Bn | 561.00 Mn |
| 9 | Tractor Supply | 16.74 Bn | 15.90 Bn | 1.68 Bn | 597.96 Mn |
| 10 | Weis Markets | 1.80 Bn | 1.00 Bn | 328.40 Mn | 61.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 61.16 Mn |
| Mar 28, 2026 | 67.16 Mn |
| Dec 27, 2025 | 73.91 Mn |
| Sep 27, 2025 | 52.31 Mn |
| Jun 28, 2025 | 60.83 Mn |
| Mar 29, 2025 | 51.40 Mn |
| Dec 28, 2024 | 70.93 Mn |
| Sep 28, 2024 | 56.31 Mn |
| Jun 29, 2024 | 59.23 Mn |
| Mar 30, 2024 | 53.79 Mn |
| Dec 30, 2023 | 52.13 Mn |
| Sep 30, 2023 | 57.10 Mn |
| Jul 1, 2023 | 73.04 Mn |
| Apr 1, 2023 | 59.31 Mn |
| Dec 31, 2022 | 60.00 Mn |
| Sep 24, 2022 | 59.75 Mn |
| Jun 25, 2022 | 74.29 Mn |
| Mar 26, 2022 | 67.04 Mn |
| Dec 25, 2021 | 55.92 Mn |
| Sep 25, 2021 | 64.93 Mn |
API Access
Weis Markets EBITDA 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=ebitda&ticker=WMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WMK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=WMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();