Netscout Systems (NTCT) EV to EBITDA (2011 - 2025)
Netscout Systems' EV to EBITDA was 8.22 in fiscal Q3 2026 (quarter ended Dec 31, 2025), up 2.2% from the prior quarter.
Netscout Systems (NTCT) EV to EBITDA (2011 - 2025) Analysis & Trends
On a trailing twelve-month basis, Netscout Systems' EV to EBITDA was -0.95 through Dec 31, 2025; for FY2023 (ended Mar 31, 2023), it came in at 9.92, down 14.4% from FY2022.
- In earlier fiscal years, EV to EBITDA was 11.59 in FY2022 (+3.5%), 11.19 in FY2021 (+13.2%), 9.89 in FY2020 (-61.3%) and 25.53 in FY2019 (+128.8%).
- Quarterly EV to EBITDA has moved between 8.04 (fiscal Q2 2026) and 14.27 (fiscal Q1 2023) over five years.
- The best year-over-year quarter for EV to EBITDA over five years was fiscal Q2 2022 (growth of 28.5%); the worst was fiscal Q1 2024 (a decline of 21.9%).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn |
| 10 | Netscout Systems | 2.82 Bn | 526.09 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 8.22 |
| Sep 30, 2025 | 8.04 |
| Jun 30, 2025 | 8.39 |
| Sep 30, 2023 | 9.97 |
| Jun 30, 2023 | 11.14 |
| Mar 31, 2023 | 9.92 |
| Dec 31, 2022 | 12.18 |
| Sep 30, 2022 | 12.65 |
| Jun 30, 2022 | 14.27 |
| Mar 31, 2022 | 11.59 |
| Dec 31, 2021 | 11.03 |
| Sep 30, 2021 | 10.14 |
| Jun 30, 2021 | 11.18 |
| Mar 31, 2021 | 11.19 |
| Dec 31, 2020 | 10.73 |
| Sep 30, 2020 | 7.89 |
| Jun 30, 2020 | 10.15 |
| Mar 31, 2020 | 9.89 |
| Dec 31, 2019 | 9.37 |
| Sep 30, 2019 | 12.00 |
Netscout Systems EV to 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=ev-to-ebitda&ticker=NTCT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "NTCT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=NTCT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();