Good Times Restaurants (GTIM) EBITDA (2010 - 2026)
Good Times Restaurants' EBITDA came in at $2.69 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 20.3% from $2.23 million a year earlier and up 151.4% from the prior quarter.
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Analysis
Good Times Restaurants (GTIM) EBITDA (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Good Times Restaurants reported EBITDA of $5.53 million, up 17.4% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $4.38 million, down 16.3% from FY2024.
- EBITDA carries a four-year compound annual growth rate of -20.4% (FY2021 to FY2025).
- Going back by fiscal year, EBITDA was $5.23 million in FY2024 (+10.9%), $4.72 million in FY2023 (+48.3%), $3.18 million in FY2022 (-70.8%) and $10.89 million in FY2021.
- The fiscal Q3 2026 figure represents the highest quarterly EBITDA since fiscal Q3 2021.
- Year-over-year, EBITDA has increased for three consecutive quarters, with growth averaging 23.4% over the last eight quarters.
- The fastest year-over-year change in EBITDA over five years came in fiscal Q2 2026 (growth of 107.6%), and the weakest in fiscal Q2 2025 (a decline of 67.7%).
- Business Quant data shows GTIM's EBITDA at $1.07 million (Q2 2026), $1.27 million (Q1 2026) and $512,000 (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 165.62 Bn | 160.44 Bn | 6.42 Bn | 3.90 Bn |
| 2 | Starbucks | 108.79 Bn | 96.42 Bn | - | 1.37 Bn |
| 3 | Chipotle Mexican Grill | 40.35 Bn | 36.33 Bn | - | 623.92 Mn |
| 4 | Yum Brands | 37.59 Bn | 34.48 Bn | 1.47 Bn | 715.00 Mn |
| 5 | Restaurant Brands International | 24.96 Bn | 22.07 Bn | 1.38 Bn | 793.00 Mn |
| 6 | Darden Restaurants | 22.28 Bn | 21.39 Bn | -113.70 Mn | 663.10 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 793.00 Mn |
| 8 | Yum China Holdings | 14.08 Bn | 8.44 Bn | 537.00 Mn | 468.00 Mn |
| 9 | Texas Roadhouse | 10.31 Bn | 9.67 Bn | - | 201.13 Mn |
| 10 | Good Times Restaurants | 15.63 Mn | 4.15 Mn | - | 2.69 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.69 Mn |
| Mar 31, 2026 | 1.07 Mn |
| Dec 30, 2025 | 1.27 Mn |
| Sep 30, 2025 | 512,000.00 |
| Jul 1, 2025 | 2.23 Mn |
| Apr 1, 2025 | 515,000.00 |
| Dec 31, 2024 | 1.12 Mn |
| Sep 24, 2024 | 848,000.00 |
| Jun 25, 2024 | 2.21 Mn |
| Mar 26, 2024 | 1.60 Mn |
| Dec 26, 2023 | 574,000.00 |
| Sep 26, 2023 | 538,000.00 |
| Jun 27, 2023 | 1.39 Mn |
| Mar 28, 2023 | 1.74 Mn |
| Dec 27, 2022 | 1.04 Mn |
| Sep 27, 2022 | -138,000.00 |
| Jun 28, 2022 | 1.84 Mn |
| Mar 29, 2022 | -873,000.00 |
| Dec 28, 2021 | 2.35 Mn |
| Sep 28, 2021 | 2.66 Mn |
API Access
Good Times Restaurants 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=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();