Noodles (NDLS) EPS (Diluted) (2012 - 2026)
Noodles' EPS (Diluted) was -$0.67 in Q2 2026, compared with -$3.04 a year earlier.
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Analysis
Noodles (NDLS) EPS (Diluted) (2012 - 2026) Analysis & Trends
On a trailing twelve-month basis, Noodles' EPS (Diluted) was -$3.94 through Jun 30, 2026; for FY2025, it came in at -$7.36.
- In earlier years, EPS (Diluted) was -$6.37 in FY2024, -$1.72 in FY2023 and $0.64 in FY2021.
- Quarterly EPS (Diluted) has moved between -$3.04 (Q2 2025) and $0.81 (Q3 2021) over five years.
- Per Business Quant data, NDLS's EPS (Diluted) in the three quarters before Q2 2026 was -$0.58 (Q1 2026), -$1.18 (Q4 2025) and -$1.58 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 199.07 Bn | 195.11 Bn | 6.47 Bn | 3.51 |
| 2 | Starbucks | 125.34 Bn | 125.35 Bn | - | 0.59 |
| 3 | Chipotle Mexican Grill | 45.50 Bn | 42.00 Bn | - | 0.27 |
| 4 | Yum Brands | 42.97 Bn | 38.79 Bn | 1.38 Bn | 5.92 |
| 5 | Restaurant Brands International | 27.07 Bn | 24.44 Bn | 1.40 Bn | 1.19 |
| 6 | Darden Restaurants | 25.87 Bn | 24.97 Bn | 1.68 Bn | 2.04 |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 2.10 |
| 8 | Yum China Holdings | 16.86 Bn | 11.73 Bn | 652.00 Mn | 0.91 |
| 9 | Texas Roadhouse | 12.35 Bn | 11.68 Bn | 1.02 Bn | 1.36 |
| 10 | Noodles | 82.94 Mn | 74.23 Mn | 90.30 Mn | -0.67 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -0.67 |
| Mar 31, 2026 | -0.58 |
| Dec 30, 2025 | -1.18 |
| Sep 30, 2025 | -1.58 |
| Jul 1, 2025 | -3.04 |
| Apr 1, 2025 | -1.58 |
| Dec 31, 2024 | -1.71 |
| Oct 1, 2024 | -1.18 |
| Jul 2, 2024 | -2.40 |
| Apr 2, 2024 | -1.09 |
| Jan 2, 2024 | -0.97 |
| Oct 3, 2023 | 0.12 |
| Jul 4, 2023 | -0.23 |
| Apr 4, 2023 | -0.54 |
| Sep 27, 2022 | 0.14 |
| Jun 28, 2022 | 0.23 |
| Mar 29, 2022 | -1.12 |
| Dec 28, 2021 | -0.82 |
| Sep 28, 2021 | 0.81 |
| Jun 29, 2021 | 0.98 |
API Access
Noodles EPS (Diluted) 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=eps-diluted&ticker=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "NDLS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=eps-diluted&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();