diff --git a/examples/kelmarsh-kaggle.py b/examples/kelmarsh-kaggle.py
new file mode 100644
index 0000000..5465c15
--- /dev/null
+++ b/examples/kelmarsh-kaggle.py
@@ -0,0 +1,44 @@
+"""Example submission for https://www.kaggle.com/competitions/predict-the-wind-speed-at-a-wind-turbine/"""
+
+import logging
+from pathlib import Path
+
+from examples.helpers import setup_logger
+from wind_up.constants import OUTPUT_DIR, PROJECTROOT_DIR
+
+CACHE_DIR = PROJECTROOT_DIR / "cache" / "kelmarsh_kaggle"
+ASSESSMENT_NAME = "kelmarsh_kaggle"
+ANALYSIS_OUTPUT_DIR = OUTPUT_DIR / ASSESSMENT_NAME
+ANALYSIS_OUTPUT_DIR.mkdir(exist_ok=True, parents=True)
+setup_logger(ANALYSIS_OUTPUT_DIR / "analysis.log")
+logger = logging.getLogger(__name__)
+
+
+def main(analysis_name: str, *, generate_custom_plots: bool = True) -> None:
+    # verify the data is in the correct location
+    data_path = Path("kelmarsh_kaggle_data")
+    expected_files = [
+        "train.csv",
+        "test.csv",
+        "sample_submission.csv",
+        "metaData.csv",
+        "blah.csv",
+    ]
+    data_ok = all((data_path / file).exists() for file in expected_files)
+    if not data_ok:
+        data_url = r"https://www.kaggle.com/competitions/predict-the-wind-speed-at-a-wind-turbine/data"
+        raise FileNotFoundError(
+            f"Expected files not found in {data_path}.\nPlease download the data from the Kaggle "
+            f"at {data_url} and save them in {data_path.resolve()}."
+        )
+
+    # assumptions below are based on Table 5.1 of Data Science for Wind Energy (Yu Ding 2020)
+    assumed_rated_power_kw = 2050  # from metaData.csv
+    assumed_rotor_diameter_m = 92  # from metaData.csv
+    cutout_ws_mps = 25  # assumption
+
+    logger.info("Unpacking turbine SCADA data")
+
+
+if __name__ == "__main__":
+    main("messin around")