Superior Group Of Companies (SGC) EBITDA (2010 - 2026)
Superior Group Of Companies (SGC) recorded EBITDA of $7.68 million in Q2 2026, up 26.6% from $6.06 million a year earlier and up 59.1% from the prior quarter.
Superior Group Of Companies (SGC) EBITDA (2010 - 2026) Analysis & Trends
On a TTM basis, Superior Group Of Companies' EBITDA came in at $28.64 million as of Jun 30, 2026, up 1.4% year-over-year; for FY2025, it was $25.74 million, down 23.9% from FY2024.
- Annual EBITDA has a five-year compound annual growth rate of -15.7% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $33.84 million in FY2024 (+1.1%), $33.48 million in FY2023 (+11.4%), $30.04 million in FY2022 (-43.6%) and $53.25 million in FY2021 (-11.8%).
- Quarterly EBITDA has ranged from $3.54 million in Q1 2025 to $13.1 million in Q3 2021 over the past five years.
- On a year-over-year basis, EBITDA has increased for three consecutive quarters, with an average decline of 1.0% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 132.2% in Q4 2023, against a decline of 65.3% in Q2 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $4.82 million (Q1 2026), $8.6 million (Q4 2025) and $7.54 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 56.18 Bn | 22.38 Bn | 4.80 Bn | 1.08 Bn |
| 2 | Tapestry | 23.99 Bn | 19.95 Bn | 1.56 Bn | 500.90 Mn |
| 3 | Ralph Lauren | 22.76 Bn | 14.85 Bn | 1.44 Bn | 401.30 Mn |
| 4 | Deckers Outdoor | 12.61 Bn | 5.48 Bn | - | - |
| 5 | Lululemon Athletica | 11.29 Bn | 5.54 Bn | 1.46 Bn | 595.99 Mn |
| 6 | Levi Strauss | 8.02 Bn | 4.60 Bn | 1.07 Bn | 277.10 Mn |
| 7 | V F | 6.86 Bn | 3.48 Bn | 917.04 Mn | -25.29 Mn |
| 8 | Gildan Activewear | 6.55 Bn | 5.47 Bn | 459.76 Mn | 244.22 Mn |
| 9 | Birkenstock Holding | 6.11 Bn | 4.43 Bn | 493.89 Mn | 326.23 Mn |
| 10 | Superior Group Of Companies | 192.50 Mn | 106.19 Mn | 56.12 Mn | 7.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.68 Mn |
| Mar 31, 2026 | 4.82 Mn |
| Dec 31, 2025 | 8.60 Mn |
| Sep 30, 2025 | 7.54 Mn |
| Jun 30, 2025 | 6.06 Mn |
| Mar 31, 2025 | 3.54 Mn |
| Dec 31, 2024 | 7.25 Mn |
| Sep 30, 2024 | 11.39 Mn |
| Jun 30, 2024 | 5.56 Mn |
| Mar 31, 2024 | 9.63 Mn |
| Dec 31, 2023 | 9.26 Mn |
| Sep 30, 2023 | 9.47 Mn |
| Jun 30, 2023 | 7.64 Mn |
| Mar 31, 2023 | 7.12 Mn |
| Dec 31, 2022 | 3.99 Mn |
| Sep 30, 2022 | 10.22 Mn |
| Jun 30, 2022 | 5.34 Mn |
| Mar 31, 2022 | 10.49 Mn |
| Dec 31, 2021 | 8.59 Mn |
| Sep 30, 2021 | 13.10 Mn |
Superior Group Of Companies 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=SGC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "SGC", "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=SGC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();