Launch angle continues to trouble me. It might trouble many of you as well, I don’t know. I’ve done a lot of research into which launch angles are the most valuable (10-26), most repeatable (<0 and >26), most common (-10 to 10), and which have the greatest exit velocity (-10 to 20).  These are round numbers, and each batter many differ with regards to their personal swing path or pitch selection.

Even with all of this, launch angle troubles me. Especially when I hear people quoting average launch angle.

In a lot of ways, average launch angle might be similar to average pitch velocity. If a pitcher throws 10% breaking balls and 90% fastballs his average velocity would be significantly higher than if he threw 90% breaking balls and 10% fastballs. Alright, 90% breaking balls is extreme, but you get my point. Maybe it is better to look at the velocity of each pitch independently: the guy has a 95mph fastball and an 84 mph curveball. That gives us a lot more information than saying he has an average velocity of, say, 91.

You have the same sort of problem when you quote average launch angle. Is the guy only hitting the ball to extremes? Maybe he only hits ground balls and pop ups, that would give you the same launch angle as a guy who only hit line drives or a guy who hit a perfectly balanced mix of ground balls, line drives, and fly balls. Using the average feels inherently wrong to me, but I haven’t been able to identify a better way to easily sum up this information. Read the rest of this entry »

Over the past three years I’ve had a lot of fun studying quality of contact stats, and I’ve tried to put everything I have learned into xStats.  This uses exit velocity, launch angle, running speed, park factors, temperature and more to measure a player’s offensive performance and displays this information in the form of basic slash line items to make it easy to understand for any baseball fan.  You’ll see stats like expected batting average, slugging, BABIP, and wOBA. (xAVG, xSLG, xBABIP, and xOBA, respectively).

Recently I’ve run 7 day, 30 day, and 60 day stats, giving an insight into players who have been out or under performing their game results in recent weeks. Today I want to touch on a few of the batters I find particularly interesting, and I’ll include a little table showing a few other notable players as well. Read the rest of this entry »

Before I get into just how completely wrong my first prediction is/was, I want to briefly explain my outlook for the Bold Predictions in the first place.  I think these should be fun and spark conversation. As a result, they should probably be controversial, at least in part. There should be a reason for each pick, and the reason shouldn’t necessarily be built on a strong hypothesis. If you have a solid reason to believe something then you aren’t talking about a bold prediction, it is just a normal prediction. Bold predictions should be built on a questionable foundation, that’s the fun part.

I view this as a testing ground for ideas. Most of these are arguments I would have otherwise quietly kept to myself. Any by quietly I mean tweeted out once and then retweeted at the end of the season if they came true. Just kidding.

Having said all that, let’s get to my first and worst prediction. Oh jeez, here we go. Read the rest of this entry »

We are officially in the second half of the season. I know, I know, people like to call the All Star Break the middle point. I can understand why, it is a natural (artificial) divider in the season in the same way a river or a mountain range may divide countries. Personally, I prefer to look at the game totals, and there are fewer ahead of us than there are behind us.

Players who got off to hot starts have mostly come back to Earth. Mostly. Aaron Judge is seems to have enough delta v to effect an Hohmann transfer, so he could be leaving Earth at any moment. Beyond that, players should be settling into their normal, expected production for the season.

Speaking of expected production, the halfway point seems to be a good time to take a look at power numbers, particularly home runs. For the past few years I have run a little side project called Citi Field Homeruns, where I meticulously track the home runs in Citi Field, aiming to measure the impact of changing ballpark dimensions. Okay, so this explanation is largely irrelevant to my goal here, other than to establish a few small pieces of information: Read the rest of this entry »

Over the past few weeks I have been working on a stat which I call OUTs.  I’m bad at naming things, I’m sorry. If you have a better name, please, help. Anyways, this stat sums weakly hit balls and strikeouts and subtracts well hit balls and walks, then divides it all by plate appearances. If you would like to see the exact formula, you can read this article.

For this stat, lower is indeed better. Also, you can convert this number to a bbFIP (batted ball FIP) by multiplying by -11 and adding 5.6. You can also convert to a Draftkings salary by multiplying by -2700 and adding 4000, although with Draftkings it is better to add and subtract the standard deviation (.3) from the OUTs score to create a range of values.

Read the rest of this entry »

This topic is an iffy area, and I want to say that up front. It is complicated and controversial.  I don’t have all of the facts, and I don’t have access to the best available data.  I’m just going to share, as best I can, the situation as I currently understand it. All of the numbers taken here are from Baseball Savant.  I’ve done nothing to manipulate the numbers in any way.  I say this because, as some of you may know, I generally run an algorithm to clean up and manipulate numbers from Baseball Savant prior to using them for analysis. Today is not one of those days, I’m just going with the raw information.

Trackman Radar, as I understand it, specializes in measuring velocity.  That is its bread and butter, and other metrics measured by Trackman are added on top of, or derived from, this most basic starting point. By all accounts, Trackman is very good radar, and these velocity measurements are very reliable.

Velocity Fluctuations

That said, there are a number of pretty large home/road exit velocity fluctuations worth pointing out.  I’m not exactly sure what may cause these differences. It could be quality of pitching or batting. If your team has great pitchers, you’d expect them to give up fewer hard hit balls, so maybe your home park exit velocity numbers would be suppressed.

Your batters could provide a similar input.  A good offensive team may have overall higher exit velocity contributions, or a bad offense may have below average. I stress *may*. A good offense isn’t necessarily defined by high exit velocity.  Look at guys like Mike Trout and Joey Votto.  Neither of these guys produce particularly high exit velocities, but both are great hitters. Likewise, Manny Machado has had elite exit velocity this season, but with pedestrian numbers.

These things are complicated, there are a lot of moving parts. A great pitching staff and a great offense may cancel each other out, for example. However, we need to talk about these home/away exit velocity numbers. Read the rest of this entry »

Over the past few days something very odd has happened in baseball. Somehow, some way, Zack Cozart has become the active fWAR leader. Okay, this may not be as big a surprise this afternoon as it may have been when you first heard about this, but it is still pretty crazy, right? Or maybe you saw him sneaking up the leaderboards over the past few days or weeks. Either way, it has happened. He’s now number one amongst the active players, and perhaps he’ll soon overtake Trout for first amongst all players.

In terms of fantasy, WAR doesn’t carry much weight, of course. Especially for a guy like Cozart who generates a solid chunk of his value through defensive excellence. Even still, Cozart is posting numbers at a rate that far exceeds his career numbers. He currently stands with a .351 batting average and a 1.059 OPS, up from his career .254 average and .704 OPS.

Zack Cozart has below average exit velocity, only 84 mph. We’re not talking a touch below average, either, he’s more than a full standard deviation below with a z-score of -1.37. All this made me curious about where exactly he sat on the exit velocity spectrum, whether there are other similar outliers, and if there is anything we can learn from them. Read the rest of this entry »

Manny Machado has been in a slump. That feels like an understatement. Over the past month he’s been one of the weakest hitters in the game, managing only .261 wOBA and 56 wRC+. This value is buoyed by six home runs, which account for 27% of his hits in the month of May. This is one of the worst stretches of his career, if not the worst. Notably, he had a rough patch to begin the 2015 season, but that period only lasted two, perhaps three weeks. It also had a reason, Machado had missed the final 80 games of 2014 while recovering from knee surgery. This year, though. This is different.

There are no obvious signs of problems with Machado.  By all accounts his mechanics seem fine and he appears to be healthy. There could be psychological issues at play and many have used the term ‘pressing’ to describe Machado. Unfortunately there is a possibility that the feud with the Red Sox and the resulting beanings and attempted beanings may have played some role in his slump, although that seems like a bit of a stretch.  None of these explanations are satisfactory, and they raise more questions than they answer.

Today I’m going to look at this slump in a slightly different manner, and hopefully highlight a few measurements and stats along the way that will spark your imagination. As usual, this piece is less about Manny Machado, and more about approaching baseball from a different perspective. Read the rest of this entry »

Last season the Cubs pitching had a great BABIP, .255, the best in MLB by quite a margin.  This has been attributed to superior defense and great pitching. Both of these seem like good enough explanations. This season, with roughly the same team, their BABIP has dropped to .286, effectively league average.

Now, there is a lot you may assume from these numbers. You may think, of course, BABIP is so unpredictable. Of course a team that was above average one season would return to average the following season.  Fair enough, you could say that. Some argue their outfield defense has taken a step back. That might be true.

These are all guesses and assumptions, but fortunately we have a few more tools for evaluating quality of contact, so let’s see what they may tell us about this Cubs pitching staff. We can use Statcast to evaluate quality of contact. When we do so, it paints a bit of a different picture.

Read the rest of this entry »

Last week I touched on a few misconceptions about launch angles and exit velocity. This article is a Part II, so you may be interested in going back and reading Part I if you haven’t already. Otherwise, allow me to summarize:

The value of batted balls drops rapidly with higher launch angles. In a sense this goes without saying, everyone knows pop ups are bad.  However, the ideal launch angle may be lower than you might expect. You’ll hear many people claim 25-30 degrees is the best range to shoot for, but even this is too high. The best angles are hit between 19 and 26 degrees. These batted balls can be referred to as fliners, somewhere between a line drive and a fly ball.

This week, I want to address the concept of the “Flyball Revolution”, why I think this is a misnomer, and which players may be suffering from this mindset. Read the rest of this entry »