Wingstop (WING) Operating Expenses (2014 - 2026)
Wingstop's Operating Expenses came in at $130.93 million for Q2 2026, up 1.4% from $129.1 million a year earlier but down 1.8% from the prior quarter.
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Analysis
Wingstop (WING) Operating Expenses (2014 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 27, 2026, Wingstop reported Operating Expenses of $519.88 million, up 3.0% year-over-year; for FY2025, it was $517.56 million, up 12.5% from FY2024.
- Operating Expenses has increased in each of the last 12 years, with a five-year compound annual growth rate of 22.0% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $460.19 million in FY2024 (+32.4%), $347.46 million in FY2023 (+30.8%), $265.59 million in FY2022 (+27.2%) and $208.75 million in FY2021 (+9.1%).
- The five-year range for quarterly Operating Expenses is $44.95 million (Q3 2021) to $133.32 million (Q1 2026).
- Year-over-year, Operating Expenses has increased for 19 consecutive quarters, with growth averaging 14.9% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2022 (growth of 52.6%), and the weakest in Q3 2021 (a decline of 9.5%).
- Business Quant data shows WING's Operating Expenses at $133.32 million (Q1 2026), $128.86 million (Q4 2025) and $126.78 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | 3.76 Bn |
| 2 | Starbucks | 110.34 Bn | 97.96 Bn | - | 8.42 Bn |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | 1.51 Bn |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 2.82 Bn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | 1.80 Bn |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | 2.88 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.80 Bn |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 2.79 Bn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 1.54 Bn |
| 10 | Wingstop | 3.58 Bn | 2.89 Bn | 160.50 Mn | 130.93 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 130.93 Mn |
| Mar 28, 2026 | 133.32 Mn |
| Dec 27, 2025 | 128.86 Mn |
| Sep 27, 2025 | 126.78 Mn |
| Jun 28, 2025 | 129.10 Mn |
| Mar 29, 2025 | 132.83 Mn |
| Dec 28, 2024 | 119.98 Mn |
| Sep 28, 2024 | 122.68 Mn |
| Jun 29, 2024 | 114.48 Mn |
| Mar 30, 2024 | 103.05 Mn |
| Dec 30, 2023 | 97.24 Mn |
| Sep 30, 2023 | 86.45 Mn |
| Jul 1, 2023 | 80.72 Mn |
| Apr 1, 2023 | 83.05 Mn |
| Dec 31, 2022 | 76.00 Mn |
| Sep 24, 2022 | 68.59 Mn |
| Jun 25, 2022 | 61.40 Mn |
| Mar 26, 2022 | 59.60 Mn |
| Dec 25, 2021 | 57.81 Mn |
| Sep 25, 2021 | 44.95 Mn |
API Access
Wingstop 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=WING&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WING", "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=WING&period=max&api_key=YOUR_API_KEY");
const data = await res.json();