GameStop (GME) Return on Sales [ROS] (2009 - 2026)
GameStop's Return on Sales [ROS] came in at 20.27% for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 13.44 percentage points from 6.83% a year earlier and up 3.12 percentage points from the prior quarter.
GameStop (GME) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Aug 1, 2026, GameStop reported Return on Sales [ROS] of 13.52%, up 10.87 percentage points year-over-year; for FY2026 (ended Jan 31, 2026), it was 6.39%, up 7.08 percentage points from FY2025.
- Return on Sales [ROS] carries a five-year change of +11.07 percentage points (FY2021 to FY2026).
- Going back by fiscal year, Return on Sales [ROS] was -0.69% in FY2025 (-0.03 pp), -0.65% in FY2024 (+4.60 pp), -5.26% in FY2023 (+0.87 pp) and -6.13% in FY2022 (-1.46 pp).
- The fiscal Q2 2027 figure represents the highest quarterly Return on Sales [ROS] in data going back to fiscal Q4 2009.
- Year-over-year, Return on Sales [ROS] has increased for seven consecutive quarters, with an average year-over-year change of +7.69 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in fiscal Q1 2027 (a gain of 18.63 percentage points), and the weakest in fiscal Q4 2022 (a drop of 8.29 percentage points).
- Business Quant data shows GME's Return on Sales [ROS] at 17.16% (Q1 2027), 12.24% (Q4 2026) and 5.03% (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn | 13.69% |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn | 14.29% |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn | 13.09% |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn | 13.67% |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn | 17.62% |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn | 9.65% |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn | 9.22% |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn | 20.15% |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn | 19.08% |
| 10 | GameStop | 11.09 Bn | -20.18 Bn | 345.00 Mn | 20.27% |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 20.27% |
| May 2, 2026 | 17.16% |
| Jan 31, 2026 | 12.24% |
| Nov 1, 2025 | 5.03% |
| Aug 2, 2025 | 6.83% |
| May 3, 2025 | -1.47% |
| Feb 1, 2025 | 6.22% |
| Nov 2, 2024 | -3.88% |
| Aug 3, 2024 | -2.76% |
| May 4, 2024 | -5.74% |
| Feb 3, 2024 | 3.08% |
| Oct 28, 2023 | -1.36% |
| Jul 29, 2023 | -1.43% |
| Apr 29, 2023 | -4.72% |
| Jan 28, 2023 | 2.08% |
| Oct 29, 2022 | -8.12% |
| Jul 30, 2022 | -9.49% |
| Apr 30, 2022 | -11.15% |
| Jan 29, 2022 | -7.40% |
| Oct 30, 2021 | -7.94% |
GameStop 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=GME&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "GME", "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=GME&period=max&api_key=YOUR_API_KEY");
const data = await res.json();