Brinker International (EAT) Return on Sales [ROS] (2009 - 2026)
Brinker International's Return on Sales [ROS] came in at 10.87% for fiscal Q4 2026 (quarter ended Jun 24, 2026), up 1.11 percentage points from 9.76% a year earlier but down 0.46 percentage points from the prior quarter.
Brinker International (EAT) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 24, 2026), Brinker International's Return on Sales [ROS] was 10.67%, up 1.17 percentage points from FY2025.
- Return on Sales [ROS] has increased in each of the last three fiscal years, with a five-year change of +4.70 percentage points (FY2021 to FY2026).
- Going back by fiscal year, Return on Sales [ROS] was 9.51% in FY2025 (+4.31 pp), 5.20% in FY2024 (+1.71 pp), 3.49% in FY2023 (-0.70 pp) and 4.19% in FY2022 (-1.78 pp).
- The five-year range for quarterly Return on Sales [ROS] is -2.07% (fiscal Q1 2023) to 11.60% (fiscal Q2 2026).
- Year-over-year, Return on Sales [ROS] has increased for 14 consecutive quarters, with an average year-over-year change of +2.76 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in fiscal Q2 2025 (a gain of 5.68 percentage points), and the weakest in fiscal Q4 2022 (a drop of 5.60 percentage points).
- Business Quant data shows EAT's Return on Sales [ROS] at 11.33% (Q3 2026), 11.60% (Q2 2026) and 8.74% (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | 47.02% |
| 2 | Starbucks | 110.34 Bn | 97.96 Bn | - | 10.52% |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | 30.20% |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 15.70% |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | 28.41% |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | 9.98% |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 28.41% |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 11.09% |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 8.50% |
| 10 | Brinker International | 8.93 Bn | 8.71 Bn | 1.14 Bn | 10.87% |
Historic Data
| Date | Value |
|---|---|
| Jun 24, 2026 | 10.87% |
| Mar 25, 2026 | 11.33% |
| Dec 24, 2025 | 11.60% |
| Sep 24, 2025 | 8.74% |
| Jun 25, 2025 | 9.76% |
| Mar 26, 2025 | 11.01% |
| Dec 25, 2024 | 11.49% |
| Sep 25, 2024 | 4.95% |
| Jun 26, 2024 | 6.05% |
| Mar 27, 2024 | 6.24% |
| Dec 27, 2023 | 5.81% |
| Sep 27, 2023 | 2.39% |
| Jun 28, 2023 | 5.51% |
| Mar 29, 2023 | 5.93% |
| Dec 28, 2022 | 3.99% |
| Sep 28, 2022 | -2.07% |
| Jun 29, 2022 | 4.38% |
| Mar 30, 2022 | 5.04% |
| Dec 29, 2021 | 4.30% |
| Sep 29, 2021 | 2.92% |
Brinker International Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=EAT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=EAT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();