Good Times Restaurants (GTIM) Return on Sales [ROS] (2010 - 2026)
Good Times Restaurants (GTIM) reported Return on Sales [ROS] of 5.02% for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 1.69 percentage points from 3.33% a year earlier and up 4.51 percentage points from the prior quarter.
Good Times Restaurants (GTIM) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Good Times Restaurants' Return on Sales [ROS] came in at 1.31%, up 0.84 percentage points year-over-year; for FY2025 (ended Sep 30, 2025), it came in at 0.23%, down 0.74 percentage points from FY2024.
- Return on Sales [ROS] has a four-year change of -5.33 percentage points (FY2021 to FY2025).
- By fiscal year, Return on Sales [ROS] came in at 0.97% in FY2024 (+0.27 pp), 0.70% in FY2023 (+1.33 pp), -0.64% in FY2022 (-6.20 pp) and 5.56% in FY2021.
- The fiscal Q3 2026 figure ranks as the highest quarterly Return on Sales [ROS] since fiscal Q3 2021.
- Year over year, Return on Sales [ROS] has now increased in each of the last three quarters, with an average year-over-year change of +0.29 percentage points over the last eight quarters.
- The high point for year-over-year Return on Sales [ROS] in five years was fiscal Q2 2023 (a gain of 8.03 percentage points); the low point was fiscal Q2 2022 (a drop of 11.17 percentage points).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at 0.52% (Q2 2026), 0.92% (Q1 2026) and -1.37% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | 47.02% |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | 10.52% |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | 15.70% |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | 30.20% |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | 28.41% |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | 9.98% |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 28.41% |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | 11.09% |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | 8.50% |
| 10 | Good Times Restaurants | 15.84 Mn | 4.36 Mn | - | 5.02% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.02% |
| Mar 31, 2026 | 0.52% |
| Dec 30, 2025 | 0.92% |
| Sep 30, 2025 | -1.37% |
| Jul 1, 2025 | 3.33% |
| Apr 1, 2025 | -1.50% |
| Dec 31, 2024 | 0.21% |
| Sep 24, 2024 | -0.33% |
| Jun 25, 2024 | 3.24% |
| Mar 26, 2024 | 1.82% |
| Dec 26, 2023 | -1.13% |
| Sep 26, 2023 | -1.18% |
| Jun 27, 2023 | 1.25% |
| Mar 28, 2023 | 2.35% |
| Dec 27, 2022 | 0.32% |
| Sep 27, 2022 | -3.03% |
| Jun 28, 2022 | 2.25% |
| Mar 29, 2022 | -5.68% |
| Dec 28, 2021 | 3.88% |
| Sep 28, 2021 | 4.73% |
Good Times Restaurants Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();