If you took a quick look at the MLB leaderboard for hard-hit rate in 2017, you would probably surmise that Nick Castellanos actually did break out, as opposed to what the headline of this post may indicate. Castellanos hit the ball hard more frequently than all but six players this season, as you can see below. The ranking by each player indicates his end-of-season rank in standard 5×5 leagues:

• J.D. Martinez – 15th – 49.2%
• Joey Gallo – 99th – 46.4%
• Aaron Judge – 5th – 45.3%
• Miguel Sano – 102nd – 45.2%
• Paul Goldschmidt – 4th – 44.4%
• Corey Seager – 66th – 44.1%
• Nick Castellanos – 65th – 43.6%

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Earlier this year I developed two closely related stats which I called OUTs and bbFIP. I’m reasonably proud of these two stats, as I feel they do a pretty good job capturing the skill of each player. They account for the numbers of weakly and strongly hit balls, balls that have high home run rates, strikeouts and walks.

In other words, it accounts for every aspect of bat generated offense, ignoring base running ability. However running speed is used to judge whether batted balls are weakly or strongly hit for each individual batter. For example, a batted balls by Billy Hamilton may be near automatic singles, whereas they would be almost guaranteed outs if hit by Albert Pujols.

The formula is constructed as follows:

$\mathrm{OUTs}=\frac{\left(.77\times \mathrm{W}\right)+\left(.17\times \mathrm{K}\right)-\left(.98\times BB\right)-\left(.69\times \mathrm{HBP}\right)-\left(1.52\times \mathrm{S}\right)-\left(2.52\times s\mathrm{HR}\right)}{\mathrm{PA}}$

Where W = weak contact (xOBA ≤ .245), S = strong contact (xOBA ≥ .634), and sHR = strong home runs (xHR% ≥ .55).

You can convert this OUTs score to an ERA scalar by multiplying by -11 and adding a constant (~5.4). This will give you what I call bbFIP, a version of FIP that is superior to standard FIP both in season and between seasons. You can also find an offense’s average OUTs score by weighting each batter by their number of plate appearances, and then translate that number to the ERA scalar to figure out how many runs you might expect them to score through the course of a season.

There are a few things to keep in mind:

1. Lower numbers are better. I tried to build this concept into the name, so it is easier to remember. It is called OUTs, outs are bad, whoever has the least of them is the best.
2. The average score is about 0.1. This season it is closer to .09.
3. The standard deviation is about 0.1.

As the 2017 regular season is coming to a close and we begin to gear up towards the 2018 season, I have a few preliminary OUTs and xOBA projections. These projections haven’t yet baked in the aging curve, so maybe ‘projection’ is the wrong word to use here. Either way, I have selected what I refer to as the ‘significantly above average’ projections in terms of OUTs. In other words, anyone who has a score less than 0. I’ve also supplied Z-Scores, xOBA, and xOBA Z-Scores. Read the rest of this entry »

Even as someone fortunate enough to have following baseball as my livelihood, I miss things. At any moment, there are 750 active major leaguers across the 30 teams and of course, there are 100s of moves of each year moving guys up and down from the minors as well as on and off the disabled list. In short, it’s a lot. It’s awesome, but it’s a lot. I picked some of my favorite seasons with at least 200 plate appearances, but also fewer than 400.

That’s the sweet spot where you can get overlooked unless you go all Matt Olson on the league. Rhys Hoskins will be among those small sample studs in the sweet spot after six more plate appearances. Neither of them made the list because they were so good that even in a small sample, they had a huge impact that simply couldn’t be ignored.

Austin Barnes, C, LAD | .284/.406/.481, 8 HR, 4 SB, 36 RBI, 32 R in 251 PA

The Dodgers backup catcher has impressed enough with the bat to draw some time at 2B. He played seven games there last year and even a game in 2015, but this year it jumped to 19 games, including four starts. He was drafted as a C2 in NL-only leagues, if at all, and he’s wound being a legitimate C2 across all formats. He’s been consistent all year, too, so even if you jumped on late, you benefitted.

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It’s the last week of the season! If you’re still fighting for a money spot, it’s not too late to take advantage of every little thing you can. The Rockies finish the season with a six game homestand, first facing the Marlins for the first three games, taking a break on Thursday, and ending with a trio of games against the Dodgers. Here are some lesser owned names that might be available in your league to consider picking up for the week, especially in a daily transaction league when you could use them only during the games at Coors for Marlins and Dodgers players.

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Earlier this week Alex Gordon hit a home run. Okay, sorry, that’s a mean joke. I am referring to the MLB single season home run record, of course. There have been more home runs hit this season than in any season in Major League Baseball history. Whether this is a good or bad thing is a matter of debate. I’ve heard from many people who are unhappy with this turn of events, others who are quite pleased, and a small minority who have no strong opinion on the matter. That third group seems to be rather small, but that’s the way of things these days.

It appears that this home run record has been spurred on by artificial means, namely an apparent change to the ball. The exact change is difficult to pin down, unfortunately. On some level it deals with the flight characteristics of the ball, though. What some call the coefficient of drag. Essentially, the air isn’t slowing down the ball as much as before. There are conflicting reports as to why this might be the case. Some say the radius of the ball is smaller. Others say the seams are smaller. Maybe both are true, maybe neither. Maybe there are other variables. It is all very much up in the air at this point. But, we do know that the ball is flying ever so slightly further now, in 2017, than it was in, say, 2015. Or 2014. Or 2013.

Perhaps counter-intuitively, very small changes in flight distance can make rather large differences in home run rate. Perhaps more intuitively, differences in flight distance can be represented as changes in effective velocity. Read the rest of this entry »

I wrote up 10 bats for the stretch run just five days ago and there is admittedly some overlap here as I go position-by-position and highlight another group of hitters you may want to add, but it’s minimal (only one is completely re-recommended, the others are essentially reminders in case they’re still available). Given that we are so short-term focused at this point, I thought even five days was enough to mention them again as they continue to standout atop the leaderboards of the last month or so.

CATCHER

Christian Vazquez, Boston Red Sox

.392/.431/.598, 4 HR, 14 RBI, 20 R, 3 SB in 109 PA over Last 30 Days (all samples will be over L30 days unless otherwise stated)

Vazquez is smacking both righties and lefties during this run, but the power comes against righties (.214 ISO). He’s hitting so well that the Sox put him at DH in a recent game to keep his bat in while getting Sandy Leon a start. Vazquez has five multi-hit games in his last seven starts (spans eight games, but one was a PH appearance).

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There are now less than two weeks left of the regular season! If you have been hesitant to sit your high priced bat that contributes in categories you don’t need in order to play the free agent pickup, don’t be. It’s totally okay to bench Khris Davis if you’re set in homers and RBI in order to try gaining a point or two in steals. Here are some lesser owned names who could chip in a couple of steals the rest of the way, which might be enough to gain you a point or two in the category.

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Jeff Zimmerman has been doing a fantastic job of looking at potential streaming pitchers down the stretch so I figured I’d take a look at some hitters who may be available for the last couple of weeks in your league. I’ll start with a group of speedsters and then look at some guys hitting for power and/or batting average of late.

Jose Reyes (46% at Yahoo!)

Reyes has a .299/.366/.505 line since July 1st with 7 HR and 11 SB and he’s been surging of late with 4 HR and 5 SB in September. He only has three hitless games in his last 20 dating back to August 13th (only 20 games because of a mid-August DL stint). He’s going to play every day and can move around your lineup with SS/3B eligibility and 2B at many outlets.

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I honestly can’t believe how close we are to the end of the regular season. This is a great time of the year without question, especially if you happen to like football a bit in addition to baseball. You have the playoff races, hopefully some fantasy chases, the start of football, and the transition to Fall. Oh, and then my birthday on October 24th, don’t forget please! Today, I wanted to look at some interesting second half performances that might’ve slipped your radar for any number of reasons.

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Predicting bat speed using the publicly available Statcast data is easier said than done. For much of the past few years there was a section on Baseball Savant which displayed a bat speed number of each player, but without much explanation for how it may be calculated. I haven’t inquired for an explanation, but I feel rather comfortable saying it was probably a derived stat using a formula published by Alan Nathan.

This formula takes the pitch speed and batted ball speed, and manipulates them using laboratory tested values for the various relevant coefficients–basically the bounciness of the ball and the bounciness of the bat. If you assume values for those coefficients, you can get a rough estimate for bat speed by plugging in the pitch speed and batted ball speed.

I don’t have proof that this is how bat speed was being estimated by Baseball Savant, but I feel it is the most likely explanation for the numbers.

Two weeks ago I proposed a formula for estimating future exit velocity using past exit velocity and launch angles. This method is far from perfect, and there is a whole lot more research that can be conducted into this area.

Over the past week I have been thinking about what performance changes may or may not be predictable from one season to another. Part of the variance that we see from season to season are large dips or climbs in offensive production, which often in retrospect we might be able to explain. Maybe there were signs that pointed towards decline, but we overlooked them for one reason or another. Maybe we didn’t know what the signs meant until further research had been conducted.

No doubt, these mistakes are often due to a lack of information. In some cases it may be bat speed. We don’t really know how much of a role bat speed plays between seasons or during the course of a career. We don’t know how injury plays a role with bat speed, nor do we understand the aging curve. Read the rest of this entry »