Gaming & Leisure Properties (GLPI) Change in Accured Expenses (2012 - 2026)
Gaming & Leisure Properties (GLPI) posted Change in Accured Expenses of $35.42 million for Q2 2026, up 73.0% from $20.47 million a year earlier.
Gaming & Leisure Properties (GLPI) Change in Accured Expenses (2012 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Gaming & Leisure Properties was $23.2 million, up 259.2% year-over-year; for FY2025, it came in at $501,000, down 97.8% from FY2024.
- Annual Change in Accured Expenses shows a five-year compound annual growth rate of -46.6% (FY2020 to FY2025).
- In prior years, Gaming & Leisure Properties' Change in Accured Expenses was $22.64 million in FY2024, $815,000 in FY2023 (-92.2%), $10.49 million in FY2022 and -$3.41 million in FY2021.
- Quarterly Change in Accured Expenses has run from a low of -$38.6 million in Q3 2025 to a high of $51.23 million in Q4 2025 over five years.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q2 2024, with growth of 425.2%; the weakest was Q3 2021, with a decline of 66.9%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$24.85 million (Q1 2026), $51.23 million (Q4 2025) and -$38.6 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 164.16 Bn | 146.67 Bn | 1.39 Bn | - |
| 2 | Prologis | 120.28 Bn | 124.68 Bn | - | 187.04 Mn |
| 3 | Simon Property | 68.97 Bn | 70.18 Bn | - | -301.36 Mn |
| 4 | Realty Income | 51.22 Bn | 53.60 Bn | - | 130.70 Mn |
| 5 | Public Storage | 49.85 Bn | 48.94 Bn | - | 144.79 Mn |
| 6 | Ventas | 43.09 Bn | 42.28 Bn | - | 49.02 Mn |
| 7 | Extra Space Storage | 28.15 Bn | 28.15 Bn | 642.43 Mn | 69.91 Mn |
| 8 | Vici Properties | 24.95 Bn | 23.07 Bn | 1.05 Bn | 47.28 Mn |
| 9 | Vivmark Residential | 22.41 Bn | 22.60 Bn | - | -25.21 Mn |
| 10 | Gaming & Leisure Properties | 10.96 Bn | 11.36 Bn | - | 35.42 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 35.42 Mn |
| Mar 31, 2026 | -24.85 Mn |
| Dec 31, 2025 | 51.23 Mn |
| Sep 30, 2025 | -38.60 Mn |
| Jun 30, 2025 | 20.47 Mn |
| Mar 31, 2025 | -32.60 Mn |
| Dec 31, 2024 | 10.10 Mn |
| Sep 30, 2024 | 8.49 Mn |
| Jun 30, 2024 | 9.74 Mn |
| Mar 31, 2024 | -5.69 Mn |
| Dec 31, 2023 | 4.91 Mn |
| Sep 30, 2023 | -1.15 Mn |
| Jun 30, 2023 | 1.86 Mn |
| Mar 31, 2023 | -4.80 Mn |
| Dec 31, 2022 | -4.36 Mn |
| Sep 30, 2022 | 29.71 Mn |
| Jun 30, 2022 | -32.24 Mn |
| Mar 31, 2022 | 17.38 Mn |
| Dec 31, 2021 | -12.57 Mn |
| Sep 30, 2021 | 10.84 Mn |
Gaming & Leisure Properties Change in Accured 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=change-in-accured-expenses&ticker=GLPI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "GLPI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=GLPI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();