Latham (SWIM) EBITDA (2020 - 2026)
Latham (SWIM) posted EBITDA of $38.76 million for Q2 2026, up 3.6% from $37.42 million a year earlier and up 499.5% from the prior quarter.
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Analysis
Latham (SWIM) EBITDA (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 27, 2026, EBITDA at Latham was $82.27 million, up 19.7% year-over-year; for FY2025, it came in at $81.93 million, up 30.6% from FY2024.
- Annual EBITDA shows a five-year compound annual growth rate of 4.7% (FY2020 to FY2025).
- In prior years, Latham's EBITDA was $62.72 million in FY2024 (+10.3%), $56.88 million in FY2023 (-16.6%), $68.19 million in FY2022 and -$3.95 million in FY2021.
- The Q2 2026 figure stands as the highest quarterly EBITDA in data going back to Q1 2020.
- On a year-over-year basis, EBITDA increased in three of the last six quarters, with growth averaging 4.7%.
- The strongest year-over-year quarter for EBITDA in the past five years was Q3 2022, with growth of 533.3%; the weakest was Q3 2021, with a decline of 83.0%.
- According to Business Quant data, EBITDA for the three prior quarters was $6.47 million (Q1 2026), $2.65 million (Q4 2025) and $34.39 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 101.69 Bn | 96.41 Bn | 2.26 Bn | 1.33 Bn |
| 2 | Johnson Controls International | 89.48 Bn | 87.21 Bn | 2.47 Bn | 1.15 Bn |
| 3 | Comfort Systems Usa | 49.70 Bn | 44.95 Bn | 844.23 Mn | 601.51 Mn |
| 4 | Carrier Global | 45.94 Bn | 40.25 Bn | 1.94 Bn | 1.14 Bn |
| 5 | Otis Worldwide | 27.46 Bn | 23.88 Bn | 1.14 Bn | 617.00 Mn |
| 6 | James Hardie Industries | 15.28 Bn | 14.34 Bn | 548.70 Mn | 386.50 Mn |
| 7 | Masco | 14.83 Bn | 12.69 Bn | 868.00 Mn | - |
| 8 | Carlisle Companies | 13.51 Bn | 9.85 Bn | 568.40 Mn | 401.20 Mn |
| 9 | Allegion | 13.35 Bn | 12.06 Bn | 517.50 Mn | 290.40 Mn |
| 10 | Latham | 740.10 Mn | 740.10 Mn | 70.08 Mn | 39.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 39.19 Mn |
| Mar 28, 2026 | 6.90 Mn |
| Dec 31, 2025 | 3.08 Mn |
| Sep 27, 2025 | 34.82 Mn |
| Jun 28, 2025 | 37.85 Mn |
| Mar 29, 2025 | 7.90 Mn |
| Dec 31, 2024 | -441,000.00 |
| Sep 28, 2024 | 25.13 Mn |
| Jun 29, 2024 | 31.03 Mn |
| Mar 30, 2024 | 8.73 Mn |
| Dec 31, 2023 | 2.38 Mn |
| Sep 30, 2023 | 29.01 Mn |
| Jul 1, 2023 | 23.85 Mn |
| Apr 1, 2023 | 3.37 Mn |
| Dec 31, 2022 | -10.64 Mn |
| Oct 1, 2022 | 34.96 Mn |
| Jul 2, 2022 | 28.86 Mn |
| Apr 2, 2022 | 16.57 Mn |
| Dec 31, 2021 | -1.82 Mn |
| Oct 2, 2021 | 5.66 Mn |
API Access
Latham 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=SWIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "SWIM", "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=SWIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();