Good Times Restaurants (GTIM) Land & Improvements (2010 - 2026)
Good Times Restaurants' Land & Improvements was $1.11 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), unchanged from $1.11 million a year earlier and unchanged from the prior quarter.
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Analysis
Good Times Restaurants (GTIM) Land & Improvements (2010 - 2026) Analysis & Trends
From fiscal Q4 2010 onward, Good Times Restaurants has reported Land & Improvements for 35 quarters.
- Land & Improvements shows a five-year compound annual growth rate of -25.0% (FY2020 to FY2025).
- In earlier fiscal years, Land & Improvements was $1.11 million in FY2024 (+6.0%), $1.05 million in FY2023 (-77.5%), $4.67 million in FY2022 (-0.7%) and $4.7 million in FY2021 (unchanged).
- Quarterly Land & Improvements has moved between $1.05 million (fiscal Q4 2023) and $6.1 million (fiscal Q3 2024) over five years.
- Compared with a year earlier, Land & Improvements was higher in 1 of the last eight quarters, with an average decline of 29.6%.
- The best year-over-year quarter for Land & Improvements over five years was fiscal Q3 2024 (growth of 30.7%); the worst was fiscal Q3 2025 (a decline of 81.8%).
- Per Business Quant data, GTIM's Land & Improvements in the three fiscal quarters before Q3 2026 was $1.11 million (Q2 2026), $1.11 million (Q1 2026) and $1.11 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Land & Improvements (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | - |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | - |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | - |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | - |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | - |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | - |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | - |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | - |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | - |
| 10 | Good Times Restaurants | 15.84 Mn | 4.36 Mn | - | 1.11 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.11 Mn |
| Mar 31, 2026 | 1.11 Mn |
| Dec 30, 2025 | 1.11 Mn |
| Sep 30, 2025 | 1.11 Mn |
| Jul 1, 2025 | 1.11 Mn |
| Apr 1, 2025 | 1.11 Mn |
| Dec 31, 2024 | 1.11 Mn |
| Sep 24, 2024 | 1.11 Mn |
| Jun 25, 2024 | 6.10 Mn |
| Mar 26, 2024 | 5.72 Mn |
| Dec 26, 2023 | 5.72 Mn |
| Sep 26, 2023 | 1.05 Mn |
| Jun 27, 2023 | 4.67 Mn |
| Mar 28, 2023 | 4.67 Mn |
| Dec 27, 2022 | 4.67 Mn |
| Sep 27, 2022 | 4.67 Mn |
| Jun 28, 2022 | 4.67 Mn |
| Mar 29, 2022 | 4.67 Mn |
| Dec 28, 2021 | 4.67 Mn |
| Sep 28, 2021 | 4.70 Mn |
API Access
Good Times Restaurants Land & Improvements 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=land-and-improvements&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "land-and-improvements", "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=land-and-improvements&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();