First Weekend Results for PyPick at Oaklawn Park

In previous Oaklawn Park racing seasons, I went through the picks of the OakPick Monte Carlo program race by race. That process was time consuming and frustrating. First, I had to compile the results in a spreadsheet. The next step was composing a blog post with horse names, winning prices, etc. Finally, the statistics were discussed and theories expounded upon.

With a new program (PyPick), I have decided to "open source" my spreadsheet. This means I simply link to the file and everyone can see for themselves how the program is doing. Without further ado, here is the link to the PyPick Cumulative Statistics Spreadsheet.

As you can see for yourself, the $2 Win bet strategy on the top pick was a profitable one for the first weekend. The other two strategies (Exacta Key Box and Trifecta Key Box) were not. I will continue to those for a little while longer. To be honest, I was kind of hoping for abject failure - so I wouldn't feel the need to do the picks. That point may come later in the season, but the first weekend demonstrates that I need further testing.

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Speaking of open source software, a piece of code that I wrote with my first student intern at Sandia National Laboratories was recently released under a BSD 3-Clause open source license. Here is the link to MatMCNP for those that have the need or want for isotopic descriptions of materials.