Brinker International (EAT) Change in Accured Expenses (2009 - 2026)
Brinker International's Change in Accured Expenses was $8.9 million in fiscal Q4 2026 (quarter ended Jun 24, 2026), up 11.3% from $8 million a year earlier but down 19.8% from the prior quarter.
Brinker International (EAT) Change in Accured Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 24, 2026), Change in Accured Expenses at Brinker International came in at -$10 million.
- In earlier fiscal years, Change in Accured Expenses was $25.7 million in FY2025 (+4.0%), $24.7 million in FY2024 (+147.0%), $10 million in FY2023 and -$11.5 million in FY2022.
- Quarterly Change in Accured Expenses has moved between -$49 million (fiscal Q1 2026) and $38.5 million (fiscal Q2 2024) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in 1 of the last five quarters, with an average decline of 30.1%.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q4 2026 (growth of 11.3%); the worst was fiscal Q4 2022 (a decline of 73.3%).
- Per Business Quant data, EAT's Change in Accured Expenses in the three fiscal quarters before Q4 2026 was $11.1 million (Q3 2026), $19 million (Q2 2026) and -$49 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | - |
| 2 | Starbucks | 110.34 Bn | 97.96 Bn | - | - |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | 4.00 Mn |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 100.69 Mn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | -8.00 Mn |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | -51.80 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | -8.00 Mn |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 107.00 Mn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 15.18 Mn |
| 10 | Brinker International | 8.93 Bn | 8.71 Bn | 1.14 Bn | 8.90 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 24, 2026 | 8.90 Mn |
| Mar 25, 2026 | 11.10 Mn |
| Dec 24, 2025 | 19.00 Mn |
| Sep 24, 2025 | -49.00 Mn |
| Jun 25, 2025 | 8.00 Mn |
| Mar 26, 2025 | 22.20 Mn |
| Dec 25, 2024 | 28.40 Mn |
| Sep 25, 2024 | -32.90 Mn |
| Jun 26, 2024 | 16.90 Mn |
| Mar 27, 2024 | -8.70 Mn |
| Dec 27, 2023 | 38.50 Mn |
| Sep 27, 2023 | -22.00 Mn |
| Jun 28, 2023 | -4.60 Mn |
| Mar 29, 2023 | 34.80 Mn |
| Dec 28, 2022 | -38.90 Mn |
| Sep 28, 2022 | 18.70 Mn |
| Jun 29, 2022 | 2.80 Mn |
| Mar 30, 2022 | 34.70 Mn |
| Dec 29, 2021 | -24.20 Mn |
| Sep 29, 2021 | -24.80 Mn |
Brinker International 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=EAT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "EAT", "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=EAT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();