Good Times Restaurants (GTIM) Operating Leases (2020 - 2026)
Good Times Restaurants' Operating Leases came in at $29.37 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 15.1% from $34.58 million a year earlier and down 5.2% from the prior quarter.
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Analysis
Good Times Restaurants (GTIM) Operating Leases (2020 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Good Times Restaurants' Operating Leases was $33.23 million, down 11.2% from FY2024.
- Operating Leases has declined in each of the last five fiscal years, with a five-year compound annual growth rate of -9.2% (FY2020 to FY2025).
- Going back by fiscal year, Operating Leases was $37.4 million in FY2024 (-11.7%), $42.33 million in FY2023 (-7.1%), $45.54 million in FY2022 (-8.4%) and $49.72 million in FY2021 (-7.5%).
- The fiscal Q3 2026 figure represents the lowest quarterly Operating Leases in data going back to fiscal Q4 2020.
- Year-over-year, Operating Leases has declined for 20 consecutive quarters, with an average decline of 12.2% over the last eight quarters.
- Over the past five years, the year-over-year decline in Operating Leases ranged from 6.0% (fiscal Q1 2024) to 16.7% (fiscal Q1 2026).
- Business Quant data shows GTIM's Operating Leases at $30.99 million (Q2 2026), $31.64 million (Q1 2026) and $33.23 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 165.62 Bn | 160.44 Bn | 6.42 Bn |
| 2 | Starbucks | 108.79 Bn | 96.42 Bn | - |
| 3 | Chipotle Mexican Grill | 40.35 Bn | 36.33 Bn | - |
| 4 | Yum Brands | 37.59 Bn | 34.48 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 24.96 Bn | 22.07 Bn | 1.38 Bn |
| 6 | Darden Restaurants | 22.28 Bn | 21.39 Bn | -113.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn |
| 8 | Yum China Holdings | 14.08 Bn | 8.44 Bn | 537.00 Mn |
| 9 | Texas Roadhouse | 10.31 Bn | 9.67 Bn | - |
| 10 | Good Times Restaurants | 15.63 Mn | 4.15 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 29.37 Mn |
| Mar 31, 2026 | 30.99 Mn |
| Dec 30, 2025 | 31.64 Mn |
| Sep 30, 2025 | 33.23 Mn |
| Jul 1, 2025 | 34.58 Mn |
| Apr 1, 2025 | 36.38 Mn |
| Dec 31, 2024 | 37.98 Mn |
| Sep 24, 2024 | 37.40 Mn |
| Jun 25, 2024 | 39.31 Mn |
| Mar 26, 2024 | 39.88 Mn |
| Dec 26, 2023 | 41.20 Mn |
| Sep 26, 2023 | 42.33 Mn |
| Jun 27, 2023 | 43.68 Mn |
| Mar 28, 2023 | 43.06 Mn |
| Dec 27, 2022 | 43.85 Mn |
| Sep 27, 2022 | 45.54 Mn |
| Jun 28, 2022 | 46.86 Mn |
| Mar 29, 2022 | 48.22 Mn |
| Dec 28, 2021 | 48.78 Mn |
| Sep 28, 2021 | 49.72 Mn |
API Access
Good Times Restaurants 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=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "ticker": "GTIM", "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=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();