Noodles (NDLS) Property, Plant & Equipment (Net) (2013 - 2026)
Noodles (NDLS) reported Property, Plant & Equipment (Net) of $94.4 million for Q2 2026, down 23.2% from $122.94 million a year earlier and down 7.9% from the prior quarter.
Noodles (NDLS) Property, Plant & Equipment (Net) (2013 - 2026) Analysis & Trends
At the end of FY2025, Noodles posted Property, Plant & Equipment (Net) of $107.36 million, down 21.8% from FY2024.
- Property, Plant & Equipment (Net) has a five-year compound annual growth rate of -2.7% (FY2020 to FY2025).
- By year, Property, Plant & Equipment (Net) came in at $137.24 million in FY2024 (-9.8%), $152.18 million in FY2023 and $119.28 million in FY2021 (-3.0%).
- The Q2 2026 figure ranks as the lowest quarterly Property, Plant & Equipment (Net) in data going back to Q4 2012.
- Year over year, Property, Plant & Equipment (Net) has now declined in each of the last seven quarters, with an average decline of 17.1% over the last seven quarters.
- The year-over-year decline in Property, Plant & Equipment (Net) has ranged between 1.5% (Q3 2021) and 25.5% (Q1 2026) over the last five years.
- Per Business Quant data, the three quarters before Q2 2026 came in at $102.5 million (Q1 2026), $107.36 million (Q4 2025) and $114.48 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | 28.48 Bn |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | 6.99 Bn |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | 2.87 Bn |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | 1.61 Bn |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | 2.23 Bn |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | 5.12 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 2.23 Bn |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | 2.62 Bn |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | 1.89 Bn |
| 10 | Noodles | 79.95 Mn | 71.25 Mn | 90.30 Mn | 94.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 94.40 Mn |
| Mar 31, 2026 | 102.50 Mn |
| Dec 30, 2025 | 107.36 Mn |
| Sep 30, 2025 | 114.48 Mn |
| Jul 1, 2025 | 122.94 Mn |
| Apr 1, 2025 | 137.58 Mn |
| Dec 31, 2024 | 137.24 Mn |
| Oct 1, 2024 | 139.77 Mn |
| Jul 2, 2024 | 139.99 Mn |
| Apr 2, 2024 | 151.32 Mn |
| Jan 2, 2024 | 152.18 Mn |
| Oct 3, 2023 | 149.44 Mn |
| Jul 4, 2023 | 140.05 Mn |
| Apr 4, 2023 | 134.72 Mn |
| Jan 3, 2023 | 129.39 Mn |
| Sep 27, 2022 | 124.43 Mn |
| Jun 28, 2022 | 124.03 Mn |
| Mar 29, 2022 | 122.32 Mn |
| Dec 28, 2021 | 119.28 Mn |
| Sep 28, 2021 | 121.59 Mn |
Noodles Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=NDLS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "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=property-plant-and-equipment-net&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();