Everything You Could Have Learned This Week

While walk rates have tended to hold fairly flat in September, strikeout rates have traditionally spiked in the final month of the season. Aside from an anomaly in 2011, run scoring has tended to decrease fairly dramatically too as the regular season winds to a close. Perhaps this phenomenon suggests that September call-up pitchers have been ahead of their called-up batter counterparts. Or perhaps as the season’s games become more meaningful down the stretch, managers have ridden their better arms more heavily to increase the league-wide pitching talent level. Whatever the reason, it is clear that at least in recent history, the month of September has suppressed offense relative to the rest of the season.

What's fascinating is that when a reliever had to pace himself, he was clearly using a different, pitch-to-contact approach, but overall results weren't affected much. The way in which he got outs changed somewhat from strikeouts to ground outs and pop flies, and the way he put runners on first changed from walks to singles, but the results were just different. Not better or worse.

Now, the question is usually asked about the elite pitchers. Scherzer and Chapman. The guys in this sample are bouncing around roles in the bullpen, probably picking up whatever work happens to be available. They're probably not elite. They're probably doing that job not because the manager thinks they are perfect for the gig, but because the team needed warm bodies to go out there and do it. The idea of pitching to contact makes sense given the demands of the assignment, so maybe it's just reasonable professionals doing what needs to be done. Interpret with care.

How much can they help/hurt?

“They can certainly help, without question. A kid like Byron Buxton was going to be a high first round pick because of the 80 speed and ridiculous athleticism, but his performance in the Under-Armour game in 2011 and the East Coast Pro event really put him on the map, and it helped alleviate some of the concerns of him being only so-so in the regular season against bad competition the next year.

As good as the coverage is for our teams and as hard as we work to make sure we cover the country along with the ability to use video, there are always going to be guy that we just don’t get as good of view of. That’s why something like the Area Code Games and Jupiter Showcase can make such a big difference; it’s a chance to see these kids for multiple games, and I think that’s sort of invaluable if only because it gives you such a good starting point when the regular season starts.

Though there is a slight downward trend of decreasing whiff rate as the standard deviation of pace increases, the trend is not significant. The confidence interval around the trend gets pretty big as the standard deviation of pace gets away from the cluster around 10 seconds. There is also a large amount of variation in whiff rate - from Alexi Ogando at 0 percent to Carter Capps at 28.3 percent. At this point, with this sample of data, I'm not willing to draw any conclusions.

I don't think this is a reason to stop looking into pace. This was such a small sample of data that wasn't really random, but I needed a smaller sample to establish the methodology in an expeditious manner. In the future, I will look at a larger sample of data while also looking at other outcomes. Now that the methodology is established, it should be easier to manipulate a larger sample of data.

Baseball has had a long and complicated relationship with the walk. Walks are undeniably positive events (for the hitting team), but they have always had the reputation of… well, it’s just a walk. It’s not that walks are the greatest thing in the world, but they certainly do have value. Like everything else, that value should be put in its proper place. But right now, it looks like the walk shortage is not just some random fluctuation. It looks like we’ve entered a period of time where batters, as a whole, are engaging in behaviors that make walks less likely, although not necessarily the same ones that make strikeouts more likely.

Toronto appeared to have Mauer shifted the most aggressively, but for the most part, we're not seeing anything too crazy. If this is a trend that teams are heading toward, it appears to be in its infancy, as we're currently only seeing it applied in the most extreme of cases and by only a few teams.

While this may be the case in the big leagues, some teams are already experimenting with outfield defense in the minors. Last September, Sam Fuld suggested to Eno Sarris that we might not be far away from a world in which corner outfielders would switch positions in the middle of a game based on the hitter's tendencies and the defensive strengths and weaknesses of the two outfielders. Shortly after Sarris' article, Gabe Kapler—employed by FOX Sports at the time—wrote a post about organizations effectively communicating information and ideas to their players. Kapler wrote specifically about the idea proposed by Fuld and how getting organizational buy-in could lead to implementing what would be considered by many to be a radical concept.

We don’t have the debut date for every pitcher in the PITCHf/x era, but we do have 303 pitchers listed. The average debut starter started the game off with 1.3 mph better velocity than he showed in the fifth inning of the same game. That’s a full tick more than the average starter has lost, in-game, this season. So your rookie starter comes out pumping about a tick more than you would expect him to show, based probably on adrenaline.

Later in the rookie season, that same starter will be about three-quarters of a mile per hour below his first inning numbers. That’s despite the fact that velocity peaks in August, and most veteran starters ramp up the velocity slowly as the season goes on. So it does look like rookie starters live on adrenaline for that first start.

Strangely, the projections are doing fine at the player level. Neither hitter nor pitcher projections are necessarily to blame for the downturn in team-level forecasts. If anything, PECOTA is better now at projecting rate statistics for batters than it was five years ago, and at the very least it has gotten no worse on the pitching side. Likewise, PECOTA’s ability to nail playing-time estimates (both plate appearances and innings pitched) has only improved over that span. So in the aggregate, it’s hard to detect the slump in team projection accuracy by looking at the performance of individual player forecasts.

But while PECOTA’s absolute prediction errors are getting smaller across the entire population of MLB players, its squared errors — a gauge more sensitive to outliers — have increased over the last five seasons. For that kind of discrepancy to exist, there can be only one explanation: The big misses are getting bigger, at least relative to the normal, everyday misses. And, notably, more of those extreme errors come when predicting the performance of young players.