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:

• 0.286 — David Peralta batting against Rick Porcello.
• 0.276 — J.D. Martinez batting against Zachary Godley.
• 0.275 — Adam Jones batting against Rick Porcello.
• 0.271 — Cody Bellinger batting against Tyler Anderson.
• 0.268 — Willians Astudillo batting against Nick Pivetta.
• 0.268 — Eddie Rosario batting against Nick Pivetta.
• 0.266 — Starlin Castro batting against Kevin Gausman.
• 0.266 — Jorge Polanco batting against Nick Pivetta.
• 0.265 — Jose Altuve batting against Frankie Montas.
• 0.261 — Christian Yelich batting against Jose Quintana.

The top four in this list all are off to very good starts with long hit streaks. That brings up a very important question about strategy; should you avoid a hitter with a long hit streak, since that streak is probably ending? The answer depends on how you view the influence of the previous games on the batter. In a game of roulette, the previous spins of the wheel have no influence on the current spin. Black is still as likely to come up as red. I suspect day to day performace is more independent than not. The best predictor in the NN model is long term performance. So depend too much on recent history.

Here are the neural network picks:

• 0.286, 0.702 — David Peralta batting against Rick Porcello.
• 0.276, 0.698 — J.D. Martinez batting against Zachary Godley.
• 0.265, 0.689 — Jose Altuve batting against Frankie Montas.
• 0.275, 0.687 — Adam Jones batting against Rick Porcello.
• 0.266, 0.677 — Starlin Castro batting against Kevin Gausman.
• 0.261, 0.675 — Christian Yelich batting against Jose Quintana.
• 0.268, 0.673 — Eddie Rosario batting against Nick Pivetta.
• 0.253, 0.672 — Charlie Blackmon batting against Kenta Maeda.
• 0.257, 0.672 — Yulieski Gurriel batting against Frankie Montas.
• 0.256, 0.671 — Michael Brantley batting against Frankie Montas.
• 0.241, 0.671 — Jean Segura batting against Jake Odorizzi.

Peralta is the unanimous pick, with J.D. Martinez second choice. Note how the NN handles Jose Altuve differently. The even weighting of long and short performance puts him near the bottom of the list, but the NN found the long-term performance a better indicator and moves Altuve near the top.

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

from baseballmusings.com http://bit.ly/2uLa0D4