Noodles (NDLS) Price to Book (2013 - 2024)
Noodles' (NDLS) Price to Book stood at 14.31 in Q3 2024, up 90.2% from the prior quarter.
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Analysis
Noodles (NDLS) Price to Book (2013 - 2024) Analysis & Trends
For FY2023, Noodles' Price to Book came in at 5.15.
- Across earlier years, Price to Book came in at 11.21 in FY2021 (-4.5%), 11.73 in FY2020 (+142.6%) and 4.83 in FY2019 (-17.1%).
- The Q3 2024 figure is the highest quarterly Price to Book since Q2 2021.
- Peak year-over-year performance for Price to Book in the last five years was growth of 257.7% in Q1 2021, against a decline of 23.5% in Q1 2020 at the low end.
- Per Business Quant, the preceding three quarters came in at 7.52 (Q2 2024), 3.73 (Q1 2024) and 5.15 (Q4 2023).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - |
| 10 | Noodles | 79.06 Mn | 70.36 Mn | 90.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Oct 1, 2024 | 14.31 |
| Jul 2, 2024 | 7.52 |
| Apr 2, 2024 | 3.73 |
| Jan 2, 2024 | 5.15 |
| Oct 3, 2023 | 3.15 |
| Jul 4, 2023 | 4.38 |
| Apr 4, 2023 | 6.40 |
| Jan 3, 2023 | 6.64 |
| Sep 27, 2022 | 5.93 |
| Jun 28, 2022 | 6.35 |
| Mar 29, 2022 | 8.48 |
| Dec 28, 2021 | 11.21 |
| Sep 28, 2021 | 13.61 |
| Jun 29, 2021 | 16.00 |
| Mar 30, 2021 | 16.57 |
| Dec 29, 2020 | 11.73 |
| Sep 29, 2020 | 9.45 |
| Jun 30, 2020 | 8.31 |
| Mar 31, 2020 | 4.63 |
| Dec 31, 2019 | 4.83 |
API Access
Noodles Price to Book 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=price-to-book&ticker=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-book", "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=price-to-book&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();