Not Feeling The Buzz

Code for Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks

Environment Installation / Requirements

Requirements

FixedEffectModel==0.0.5
jupyter==1.0.0
linearmodels==6.0
numpy==2.0.0
pandas==2.2.2
requests==2.32.3
scikit-learn==1.5.1
seaborn==0.13.2
tqdm==4.66.4
openpyxl==3.1.5

To install a new environment with the required packages, run the following commands:

1. Create a new environment using conda

(assuming miniconda installed on machine: https://docs.anaconda.com/miniconda/ )

conda create --name conda-python-buzz-env python

2. Activate the environment

conda activate conda-python-buzz-env

3. Install the required packages

Using the requirements.txt file:

pip install -r requirements.txt

Or using the install.sh script:

install.sh

File Description

Files are ordered as the replication study reads.

process_data

• dataprocess_ramirez.ipynb ⟶ ramirez_matches_cleaned.csv:

  Process dataset for use in replication and correction

• dataprocess_clegg.ipynb ⟶ clegg_matches_cleaned.csv:

  Process dataset for use in extended dataset.

results

• replication_and_correction.ipynb:

  Replication: Obtain model parameters and results to verify RRS.

  Correction: Identifies, removes, and explores the effects of the problematic Hercog bet.

  Results in Tables 1-3 and Figure 1.

• extension.ipynb:

  Conducts new mispricing and inefficiency test using extended dataset.

  Results in Table 4 and Figure 2.

• p_bs.ipynb:

  Conducts a $p_{bs}$ simulation as outlined in Wunderlich and Memmert 2020.

  Results in Appendix C.

data

• ramirez_matches_cleaned.csv:

  As processed by dataprocess_ramirez.ipynb.

• clegg_matches_cleaned.csv:

  As processed by dataprocess_clegg.ipynb.