Super League Enterprise (SLE) Total Non-Current Liabilities (2021 - 2026)
Super League Enterprise (SLE) posted Total Non-Current Liabilities of $5.85 million for Q2 2026, down 53.2% from $12.5 million a year earlier but up 18.0% from the prior quarter.
Super League Enterprise (SLE) Total Non-Current Liabilities (2021 - 2026) Analysis & Trends
At the end of FY2025, Super League Enterprise's Total Non-Current Liabilities came in at $4.33 million, down 59.2% from FY2024.
- Annual Total Non-Current Liabilities shows a four-year compound annual growth rate of -8.3% (FY2021 to FY2025).
- In prior years, Super League Enterprise's Total Non-Current Liabilities was $10.61 million in FY2024 (-23.0%), $13.77 million in FY2023 (+25.1%), $11.01 million in FY2022 (+80.2%) and $6.11 million in FY2021.
- Quarterly Total Non-Current Liabilities has run from a low of $4.33 million in Q4 2025 to a high of $13.77 million in Q4 2023 over five years.
- On a year-over-year basis, Total Non-Current Liabilities has declined in each of the last three quarters, with an average decline of 17.9% over the last eight quarters.
- The strongest year-over-year quarter for Total Non-Current Liabilities in the past five years was Q4 2022, with growth of 80.2%; the weakest was Q1 2026, with a decline of 62.0%.
- According to Business Quant data, Total Non-Current Liabilities for the three prior quarters was $4.96 million (Q1 2026), $4.33 million (Q4 2025) and $9.77 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 270.20 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 170.41 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 25.59 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | 121.77 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 326.00 Mn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 37.14 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 39.77 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | 428.00 Mn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 4.77 Bn |
| 10 | Super League Enterprise | 7.52 Mn | -25.94 Mn | 1.24 Mn | 5.85 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.85 Mn |
| Mar 31, 2026 | 4.96 Mn |
| Dec 31, 2025 | 4.33 Mn |
| Sep 30, 2025 | 9.77 Mn |
| Jun 30, 2025 | 12.50 Mn |
| Mar 31, 2025 | 13.03 Mn |
| Dec 31, 2024 | 10.61 Mn |
| Sep 30, 2024 | 8.11 Mn |
| Jun 30, 2024 | 9.69 Mn |
| Mar 31, 2024 | 10.28 Mn |
| Dec 31, 2023 | 13.77 Mn |
| Sep 30, 2023 | 10.38 Mn |
| Jun 30, 2023 | 8.17 Mn |
| Mar 31, 2023 | 6.12 Mn |
| Dec 31, 2022 | 11.01 Mn |
| Sep 30, 2022 | 12.07 Mn |
| Jun 30, 2022 | 9.96 Mn |
| Mar 31, 2022 | 4.53 Mn |
| Dec 31, 2021 | 6.11 Mn |
Super League Enterprise Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=SLE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "SLE", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=SLE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();