Duluth Holdings (DLTH) Operating Leases (2019 - 2026)
Duluth Holdings (DLTH) posted Operating Leases of $71.25 million for fiscal Q2 2027 (quarter ended Aug 2, 2026), down 14.8% from $83.64 million a year earlier and down 1.1% from the prior quarter.
Duluth Holdings (DLTH) Operating Leases (2019 - 2026) Analysis & Trends
At the end of FY2026 (ended Feb 1, 2026), Duluth Holdings' Operating Leases came in at $76.01 million, down 14.8% from FY2025.
- Annual Operating Leases has declined for three consecutive fiscal years, with a five-year compound annual growth rate of -6.1% (FY2021 to FY2026).
- In prior fiscal years, Duluth Holdings' Operating Leases was $89.22 million in FY2025 (-16.2%), $106.41 million in FY2024 (-9.3%), $117.37 million in FY2023 (+9.6%) and $107.09 million in FY2022 (+2.7%).
- The fiscal Q2 2027 figure stands as the lowest quarterly Operating Leases in data going back to fiscal Q1 2020.
- On a year-over-year basis, Operating Leases has declined in each of the last 12 quarters, with an average decline of 14.7% over the last eight quarters.
- The strongest year-over-year quarter for Operating Leases in the past five years was fiscal Q2 2024, with growth of 9.9%; the weakest was fiscal Q3 2025, with a decline of 19.9%.
- According to Business Quant data, Operating Leases for the three prior fiscal quarters was $72.02 million (Q1 2027), $76.01 million (Q4 2026) and $79.5 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nike | 53.94 Bn | 19.93 Bn | 5.39 Bn |
| 2 | Tapestry | 22.74 Bn | 18.69 Bn | 1.56 Bn |
| 3 | Ralph Lauren | 21.47 Bn | 13.57 Bn | 1.44 Bn |
| 4 | Deckers Outdoor | 11.15 Bn | 4.02 Bn | - |
| 5 | Lululemon Athletica | 10.72 Bn | 4.97 Bn | 1.46 Bn |
| 6 | Levi Strauss | 7.64 Bn | 4.29 Bn | 979.10 Mn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn |
| 8 | Birkenstock Holding | 6.06 Bn | 4.37 Bn | 493.89 Mn |
| 9 | Crocs | 5.89 Bn | 5.30 Bn | 700.71 Mn |
| 10 | Duluth Holdings | 136.47 Mn | 76.26 Mn | 88.36 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 71.25 Mn |
| May 3, 2026 | 72.02 Mn |
| Feb 1, 2026 | 76.01 Mn |
| Nov 2, 2025 | 79.50 Mn |
| Aug 3, 2025 | 83.64 Mn |
| May 4, 2025 | 86.47 Mn |
| Feb 2, 2025 | 89.22 Mn |
| Oct 27, 2024 | 88.44 Mn |
| Jul 28, 2024 | 92.28 Mn |
| Apr 28, 2024 | 102.19 Mn |
| Jan 28, 2024 | 106.41 Mn |
| Oct 29, 2023 | 110.45 Mn |
| Jul 30, 2023 | 111.00 Mn |
| Apr 30, 2023 | 114.02 Mn |
| Jan 29, 2023 | 117.37 Mn |
| Oct 30, 2022 | 120.91 Mn |
| Jul 31, 2022 | 101.01 Mn |
| May 1, 2022 | 104.45 Mn |
| Jan 30, 2022 | 107.09 Mn |
| Oct 31, 2021 | 110.37 Mn |
Duluth Holdings 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=DLTH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "ticker": "DLTH", "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=DLTH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();