For the past few 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.
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.
The Log5 Method yields these top projected hit averages versus starting pitchers:
- 0.341 — Jacob Wilson batting at Kyle Hendricks.
- 0.334 — Heliot Ramos batting at Kyle Freeland.
- 0.324 — Jung Hoo Lee batting at Kyle Freeland.
- 0.318 — Isiah Kiner-Falefa batting vs. Cal Quantrill.
- 0.307 — Tyler Fitzgerald batting at Kyle Freeland.
- 0.305 — Wilmer Flores batting at Kyle Freeland.
- 0.295 — Trea Turner batting vs. Ben Brown.
- 0.294 — Freddie Freeman batting at Randy Vasquez.
- 0.293 — Alejandro Kirk batting at Matthew Liberatore.
- 0.292 — Nico Hoerner batting at Jesus Luzardo.
It looks like a good day to face a Kyle. Freeland isn’t dominating the Log5 method as he usually does. It’s probably due to the Giants employing low BA hitters who walk a good amount.
Wilson is dealing with an injury, but is not on the illjured list.
The NN produces this list of batters with a high probability of collecting at least one hit:
- 0.341, 0.756 — Jacob Wilson batting at Kyle Hendricks.
- 0.334, 0.720 — Heliot Ramos batting at Kyle Freeland.
- 0.294, 0.718 — Freddie Freeman batting at Randy Vasquez.
- 0.283, 0.717 — Luis Arraez batting vs. Justin Wrobleski.
- 0.318, 0.710 — Isiah Kiner-Falefa batting vs. Cal Quantrill.
- 0.265, 0.709 — Aaron Judge batting at Kris Bubic.
- 0.295, 0.705 — Trea Turner batting vs. Ben Brown.
- 0.324, 0.705 — Jung Hoo Lee batting at Kyle Freeland.
- 0.280, 0.704 — Jackson Merrill batting vs. Justin Wrobleski.
- 0.281, 0.699 — Jose Ramirez batting vs. Nick Lodolo.
Ramirez is tied for the longest current hit streak in the majors at ten. He collected at least one hit in 32 of his last 33 games. It looks like a Bay Area double down today, however, as Wilson and Ramos are the consensus double down picks today. Ramos strikes out quite a bit, but owns a .348 BABIP this season and .326 for his career. If Wilson winds up not playing, Ramos and Kiner-Falefa would be the double down pairing.
You can follow the NN results on this spreadsheet. I do not guarantee results. Your best pick is going to have about a 25% chance of not getting a hit. Good luck!
Oops, I put my comment on the wrong day.
Players that show up in both Log5 and NN today are Heliot Ramos, Jacob Wilson, IKF, Trea Turner, Jung Ho Lee, and Freddie Freeman.
Highest hit win percentage is Freddie Freeman and Trea Turner today @ 90.9 to 95.38%, depending upon how the scenarios play out.
~Eric
Hey Eric,
How did you end up choosing Trea Turner? Seems like he already got his hit in the 1st inning.
Looking at the numbers 0.334 AVG and 0.720 NN Heliot Ramos batting against Kyle Freeland would seem like the better choice, since he meets the .315 AVG / .707 NN requirements. Trea didn’t meet those, so I’m curious how you were able to pick him
I downloaded all of David’s picks for the 2025 MLB season so far, – not just his version of the top two picks – and I look for patterns. Sometimes, due to these patterns I can find higher percentage winners, even higher than what he considers his “best Pick.” Hence the 90% + odds I have for today on Freddie Freeman and Trea Turner.
David’s Log 5 and Neural Net algorithms are overall 73% correct for the year, when they BOTH pick the same batter and pitcher combo. When Neural Net OR Log 5 picks the batter/pitcher combo ONLY – in other words no agreement, Log5 is running at 62% correct for the year, Neural net 68% correct for a hit this year. The beauty to all this is there are some patterns that outperform these odds and I search for them.
I have found 14 scenarios so far with 77% to 95% probability using his same data.
What I do not know for sure is, “Are these patterns static and consistent, or do they move up and down with the progress of the season, in relation to his formulas. In order to test that, I am scraping, cleaning and formatting his data, for MLB years 2023 and 2024, in order to get more data to test this out. Its a dynamic world, so maybe I am right, maybe I am not, only one way to find out, run my ideas and observations for a longer period.
I could use a coffee. Its hard work, but I do share what I find and have it all in spreadsheet.