Wait – what did you just say, bro? You said I’ll never be able to show everyone how much I love and respect all mothers in the entire world, no matter how loud and angry I get? Are you kidding me, bro? No one loves and respects them more than me AND I’LL PROVE IT RIGHT NOW, BRO!
We've got a brawl underway in Colorado and Bryce Harper is at the center of it pic.twitter.com/81PcXV1cT0
This is one of my favorite times of the fantasy season, as we don’t have enough data for the collective hive to quite make up its mind on which players are good enough to keep rostered and who should stay in their streaming lane. And in these margins, there is a lot of value to be had (and drafting errors corrected) in swooping the fantasy assets that two months from now won’t be on any wires.
Let’s take a look at some players who have been valuable fantasy assets over the first ~20% of the season (using the Razzball player rater as our markers) but are still lesser-owned, as fantasy managers have yet to fully decide who should keep getting churned around the wire, and who should be acquired and kept. Read the rest of this entry »
Ahh, hope springs eternal in April, with small samples and undeserved ratios trying their best to distract us from whether someone’s talent has changed, or maybe just their luck. But one way or another, regression is coming. It might drag things to the bad, or to the good, but time (and sample) tends to remain undefeated in the long run.
With that in mind, let’s try to see which pitchers might have some pain or joy coming soon to their fantasy ratios and play the game currently sweeping the hearts and homes of the nation, according to the most recent issue of “Official-Sounding Publication Invented by the Author, Weakly”. That’s right, it’s time to play –
It’s the beginning of May, so you know what that means – It’s time to make wild declarations based on the barest amount of evidence. Let me hear ya now; AY-PRIL! AY-PRIL! AY-PRIL!
I kid, I kid. Drawing definite conclusions after 25 games might be a fool’s errand but that doesn’t mean there aren’t tea leaves to be read in regards to what we’ve seen so far, as a plethora of minute data is available to try and parse what’s been real and what’s more fake. Take power, for example. There are all sorts of small-sample shenanigans driving the current home run totals but that doesn’t mean we can’t sort out some of the chaff and see what kind of home run bread might be getting baked during the rest of the season. Read the rest of this entry »
I don’t know how many hundreds of hours I listened to Mike Shannon’s voice on the radio but I promise you no one was better at passing rain delays by telling stories and/or drinking bourbon. No one. Rest in power, Mike, you were the best. *And to answer your question; yes, since we already live in baseball heaven, Cardinal fans instead go to super-duper heaven.Read the rest of this entry »
Using baseball-savant data and some Python code, I have written a script that will loop through a pitcher’s three most recent appearances and flag any pitcher who has shown an increase in their fastball velocity. In raw form, it looks something like this:
Looking at the table above we can see that each of these three pitchers increased their fastball (“FF” in savant data) consistently over their last three appearances. Don’t believe me? You can check my work with Savant visualizations:
While I wrote more specifically about the merits of paying close attention to game-by-game fastball increases, quoting many other studies and great pieces along the way, I won’t be writing about it again here. Instead, I’ll simply show you a list of the starters and relievers who have increased game-by-game average velocity on their four-seamers and hope that you can take it from there. Sure, you could scroll through stacks of player pages to find players who have increased velocity until the cows come home, or you could write some code that will detect those increases and flag those players for you. I chose the second way. If you find it useful, I’ll do it on a more regular basis. That’s it. This post is more about the data than the words:
