Match (MTCH) Accumulated Expenses (2009 - 2026)
Match's Accumulated Expenses was $373.03 million in Q2 2026, up 6.2% from $351.37 million a year earlier and up 15.4% from the prior quarter.
Powered by 
Analysis
Match (MTCH) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Match came in at $422.05 million, up 15.6% from FY2024.
- Accumulated Expenses has now increased for three consecutive years, with a five-year compound annual growth rate of 12.7% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $365.06 million in FY2024 (+18.8%), $307.3 million in FY2023 (+6.0%), $289.94 million in FY2022 (-62.3%) and $768.37 million in FY2021 (+231.6%).
- Quarterly Accumulated Expenses has moved between $282.22 million (Q2 2023) and $768.37 million (Q4 2021) over five years.
- Compared with a year earlier, Accumulated Expenses was higher in six of the last eight quarters, with growth averaging 10.6%.
- The best year-over-year quarter for Accumulated Expenses over five years was Q1 2022 (growth of 237.9%); the worst was Q4 2022 (a decline of 62.3%).
- Per Business Quant data, MTCH's Accumulated Expenses in the three quarters before Q2 2026 was $323.3 million (Q1 2026), $422.05 million (Q4 2025) and $400.31 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 4,185.47 Bn | 3,943.00 Bn | 73.85 Bn |
| 2 | Meta Platforms | 1,794.56 Bn | 1,497.08 Bn | 49.47 Bn |
| 3 | Netflix | 292.71 Bn | 252.90 Bn | 6.52 Bn |
| 4 | Alibaba Group Holding | 251.74 Bn | 65.51 Bn | 15.11 Bn |
| 5 | Shopify | 221.57 Bn | 198.76 Bn | 1.71 Bn |
| 6 | Uber Technologies | 142.45 Bn | 114.25 Bn | 6.38 Bn |
| 7 | Booking Holdings | 124.83 Bn | 57.88 Bn | - |
| 8 | PDD Holdings | 113.76 Bn | -130.01 Bn | 9.45 Bn |
| 9 | Spotify Technology | 106.73 Bn | 64.23 Bn | 1.86 Bn |
| 10 | Match | 10.42 Bn | 6.72 Bn | 648.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 373.03 Mn |
| Mar 31, 2026 | 323.30 Mn |
| Dec 31, 2025 | 422.05 Mn |
| Sep 30, 2025 | 400.31 Mn |
| Jun 30, 2025 | 351.37 Mn |
| Mar 31, 2025 | 345.21 Mn |
| Dec 31, 2024 | 365.06 Mn |
| Sep 30, 2024 | 321.53 Mn |
| Jun 30, 2024 | 308.04 Mn |
| Mar 31, 2024 | 299.15 Mn |
| Dec 31, 2023 | 307.30 Mn |
| Sep 30, 2023 | 331.80 Mn |
| Jun 30, 2023 | 282.22 Mn |
| Mar 31, 2023 | 282.26 Mn |
| Dec 31, 2022 | 289.94 Mn |
| Sep 30, 2022 | 286.51 Mn |
| Jun 30, 2022 | 294.56 Mn |
| Mar 31, 2022 | 704.75 Mn |
| Dec 31, 2021 | 768.37 Mn |
| Sep 30, 2021 | 329.59 Mn |
API Access
Match Accumulated Expenses 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=accumulated-expenses&ticker=MTCH&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MTCH", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=MTCH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();