Beat the Streak Picks

For the past two years Baseball Musings tried to help with playing Beat the Streak. The Day by Day Database keeps track of hit streak of at least five games. In addition, two programs produce top ten lists of players with a high probability of a hit. If you find this useful, please support Baseball Musings with a donation.

Here are the top picks my programs produced for use in Beat the Streak. This post mostly explains the ideas behind the calculations. In addition, this post shows tests on the Neural Network (NN). This post discusses an NN that includes the ballpark. I updated the models, and the results of those tests are here.

For 2019, I am just going to publish the Log5 hit averages and the NN probabilities with parks factored in. I am keeping track of the results here. I added a graph that gives a visual representation of the probability and success each day.

First, the Log5 Method picks:

There is a bug in the Log5 Method, and I don’t know how it got there. I need to do some work to figure it out, and that will need to wait until this evening. My apologies.

Here are the neural network picks:

• 0.278, 0.691 — Wilson Ramos batting against Jose Urena.
• 0.275, 0.690 — David Peralta batting against Eric Lauer.
• 0.261, 0.687 — J.D. Martinez batting against Michael Fiers.
• 0.265, 0.686 — Miguel Andujar batting against Jordan Zimmermann.
• 0.271, 0.685 — Adam Jones batting against Eric Lauer.
• 0.269, 0.684 — Christian Yelich batting against Anthony DeSclafani.
• 0.256, 0.681 — Jose Altuve batting against Shelby Miller.
• 0.267, 0.681 — Lorenzo Cain batting against Anthony DeSclafani.
• 0.268, 0.680 — Anthony Rendon batting against Zach Eflin.
• 0.258, 0.678 — Michael Brantley batting against Shelby Miller.
• 0.276, 0.675 — Andrelton Simmons batting against Marco Gonzales.

Ramos is off to a hot start, 6 for 13.

I do not guarantee results. Your best pick is going to have a 25% chance of not getting a hit. Good luck!

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