Academy Sports & Outdoors (ASO) Operating Expenses (2019 - 2026)
Academy Sports & Outdoors (ASO) recorded Operating Expenses of $419.54 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 3.8% from $404.35 million a year earlier and up 3.7% from the prior quarter.
Academy Sports & Outdoors (ASO) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, Academy Sports & Outdoors' Operating Expenses came in at $1.62 billion as of Aug 1, 2026, up 5.1% year-over-year; for FY2026 (ended Jan 31, 2026), it was $1.59 billion, up 8.2% from FY2025.
- Annual Operating Expenses has increased for three straight fiscal years, with a five-year compound annual growth rate of 3.9% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $1.47 billion in FY2025 (+2.8%), $1.43 billion in FY2024 (+4.9%), $1.37 billion in FY2023 (-5.3%) and $1.44 billion in FY2022 (+9.9%).
- The fiscal Q2 2027 figure is the highest quarterly Operating Expenses in data going back to fiscal Q3 2020.
- On a year-over-year basis, Operating Expenses has increased for six consecutive quarters, with growth averaging 5.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 10.2% in fiscal Q1 2026, against a decline of 12.5% in fiscal Q2 2023 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $404.69 million (Q1 2027), $406.46 million (Q4 2026) and $393.02 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,836.12 Bn | 2,352.82 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 312.88 Bn | 306.12 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 162.09 Bn | 139.64 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 109.97 Bn | 102.93 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.48 Bn | 58.40 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 73.51 Bn | 72.60 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 70.26 Bn | 64.85 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Autozone | 51.76 Bn | 50.66 Bn | 2.52 Bn | 1.60 Bn |
| 9 | Carvana | 43.62 Bn | 34.11 Bn | 1.38 Bn | 704.00 Mn |
| 10 | Academy Sports & Outdoors | 3.75 Bn | 2.49 Bn | 665.90 Mn | 419.54 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 419.54 Mn |
| May 2, 2026 | 404.69 Mn |
| Jan 31, 2026 | 406.46 Mn |
| Nov 1, 2025 | 393.02 Mn |
| Aug 2, 2025 | 404.35 Mn |
| May 3, 2025 | 389.60 Mn |
| Feb 1, 2025 | 385.53 Mn |
| Nov 2, 2024 | 365.24 Mn |
| Aug 3, 2024 | 368.64 Mn |
| May 4, 2024 | 353.41 Mn |
| Feb 3, 2024 | 393.04 Mn |
| Oct 28, 2023 | 345.91 Mn |
| Jul 29, 2023 | 352.48 Mn |
| Apr 29, 2023 | 340.92 Mn |
| Jan 28, 2023 | 367.74 Mn |
| Oct 29, 2022 | 342.95 Mn |
| Jul 30, 2022 | 339.33 Mn |
| Apr 30, 2022 | 315.93 Mn |
| Jan 29, 2022 | 385.86 Mn |
| Oct 30, 2021 | 344.73 Mn |
Academy Sports & Outdoors Operating 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=operating-expenses&ticker=ASO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ASO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=ASO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();