Flanigans Enterprises (BDL) EBITDA (2010 - 2026)
Flanigans Enterprises' EBITDA was $5.2 million in fiscal Q3 2026 (quarter ended Jun 27, 2026), up 29.5% from $4.02 million a year earlier but down 2.9% from the prior quarter.
Flanigans Enterprises (BDL) EBITDA (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Flanigans Enterprises' EBITDA was $16.25 million through Jun 27, 2026, up 32.5% year-over-year; for FY2025 (ended Sep 27, 2025), it came in at $13.42 million, up 32.7% from FY2024.
- EBITDA shows a five-year compound annual growth rate of 17.1% (FY2020 to FY2025).
- In earlier fiscal years, EBITDA was $10.11 million in FY2024 (-4.5%), $10.59 million in FY2023 (+6.7%), $9.92 million in FY2022 (-15.3%) and $11.71 million in FY2021 (+92.3%).
- Quarterly EBITDA has moved between $1.38 million (fiscal Q4 2023) and $5.36 million (fiscal Q2 2026) over five years.
- Compared with a year earlier, EBITDA has increased for eight straight quarters, with growth averaging 31.9% over the last eight quarters.
- The best year-over-year quarter for EBITDA over five years was fiscal Q4 2025 (growth of 69.4%); the worst was fiscal Q4 2023 (a decline of 54.6%).
- Per Business Quant data, BDL's EBITDA in the three fiscal quarters before Q3 2026 was $5.36 million (Q2 2026), $2.87 million (Q1 2026) and $2.82 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 165.31 Bn | 160.13 Bn | 6.42 Bn | 3.90 Bn |
| 2 | Starbucks | 108.61 Bn | 96.24 Bn | - | 1.37 Bn |
| 3 | Chipotle Mexican Grill | 40.32 Bn | 36.30 Bn | - | 623.92 Mn |
| 4 | Yum Brands | 37.73 Bn | 34.61 Bn | 1.47 Bn | 715.00 Mn |
| 5 | Restaurant Brands International | 24.95 Bn | 22.05 Bn | 1.38 Bn | 793.00 Mn |
| 6 | Darden Restaurants | 22.46 Bn | 21.57 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 | 14.17 Bn | 8.53 Bn | 537.00 Mn | 468.00 Mn |
| 9 | Texas Roadhouse | 10.39 Bn | 9.75 Bn | - | 201.13 Mn |
| 10 | Flanigans Enterprises | 83.30 Mn | 3.04 Mn | 32.66 Mn | 5.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 5.20 Mn |
| Mar 28, 2026 | 5.36 Mn |
| Dec 27, 2025 | 2.87 Mn |
| Sep 27, 2025 | 2.82 Mn |
| Jun 28, 2025 | 4.02 Mn |
| Mar 29, 2025 | 4.68 Mn |
| Dec 28, 2024 | 1.90 Mn |
| Sep 28, 2024 | 1.67 Mn |
| Jun 29, 2024 | 3.28 Mn |
| Mar 30, 2024 | 3.51 Mn |
| Dec 30, 2023 | 1.65 Mn |
| Sep 30, 2023 | 1.38 Mn |
| Jul 1, 2023 | 3.63 Mn |
| Apr 1, 2023 | 3.56 Mn |
| Dec 31, 2022 | 2.01 Mn |
| Oct 1, 2022 | 3.04 Mn |
| Jul 2, 2022 | 2.87 Mn |
| Apr 2, 2022 | 2.57 Mn |
| Jan 1, 2022 | 1.45 Mn |
| Oct 2, 2021 | 2.72 Mn |
Flanigans Enterprises 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=BDL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "BDL", "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=BDL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();