I remember the first time I heard about Sam and Ben's project of running the Sonoma Stompers' analytics department. I immediately thought back to the last time I was in Sonoma, which was actually last summer, because my cousin was getting married there. I remember the car ride in from San Francisco and seeing the rolling hills that line the road inland, and seeing cows standing on those hills. I thought, "Man, it would be really funny if those cows would lose their footing and just roll down those hills," and at that moment, my mind made the connection to why bovine (and other types of) animals probably have hooves: So they can get better footing and don't roll down hills and become material for widely circulated GIFs.

Now that you have learned about my last trip to central California, take some time to learn some things about baseball.


Hard-hit rate related to wRC+? Sure! To line-drive rate, though? HAH no: What Hard-Hit Rate Means for Batters, by Owen Watson, FanGraphs

Someone took a shotgun to the chart. Hitters with under 15% hard-hit rates can post line-drive rates of 26%, just as hitters with 45% hard-hit rates can post line drive rates of 17%. There seems to be effectively zero predictive value to using hard-hit rate in this way. Although it might seem obvious, hard-hit rate should not be confused with line-drive rate in any way, as ground balls and fly balls can be hit hard, just as line drives can be hit softly.

Relievers have improved in recent years! Then again, so have starters. Pitchers in general, really!: Have relievers really gotten better?, by Russell Carleton, Just a Bit Outside

Looking at these graphs, we see that bullpens, writ large have improved a lot over the past few years. If you look at the top of the graph and the bottom of the graph, we see that the range of their improvement has been about 1.1 to 1.2 runs of RA/9. That's certainly nothing to sneeze at, but let's keep it in context. Starters have seen a drop almost as big. Almost.

Still, the drop for relievers has been 20 to 30 percent bigger than that for starters. It seems that the new crop of relievers really is doing a better job. While they aren't entirely responsible for the dip in offense, there's evidence to suggest that the guy in the bullpen now is better than the guy in the bullpen was 10 years ago.


Who's really the one stealing bases? It might not be who you think: The Credit Card Game, by Russell Carleton, Baseball Prospectus

This actually squares nicely with what the stolen base components of DRA found, that the pitcher was much more responsible for a stolen base than we ever really give him credit for. In fact, the pitcher seems to have almost eight times more to do with whether a runner is successful on a steal try than the catcher. Yet we always hear about catcher caught-stealing rates and never pitcher ones. In fact, for years, I justified being lukewarm on Mike Piazza’s Hall of Fame chances because of his abysmal CS rate. I guess I was wrong on that one.

There are some interesting relationships between spin on a pitch and batted ball outcomes, like curveballs that spin more tend to produce more groundballs: On Rotation, Part 2: The Effects of Spin on Pitch Outcomes, by Jonah Pernstein, FanGraphs

More spin means fewer ground balls (GB%), unless you’re talking about curveballs, in which case it means more. Remember how Collin McHugh was targeted by the Astros because his curveball spun a lot and induced more ground balls? Here’s proof of that in action. And, once again, this makes sense — a topspin-heavy pitch is harder to lift into the air, since its point of contact with the bat (which is usually moving upwards) is moving downwards; and a backspin-heavy pitch is easier to lift, since its point of contact with the bat is moving upwards.

New technology could provide a more complete picture than ever of players' bodies and physical condition: The Future of Baseball Technology, Part Two: Into the Unknown, by Jesse Wolfersberger, The Hardball Times

Athos is a good example of what a full-body analytics system could look like. Instead of focusing on one muscle or motion, the goal is to measure every movement of the body. It is probably too restricting for many players’ tastes now, but the technology will get smaller and easier to wear. Future iterations could track players during workouts and games, sending data about each muscle, looking for warning signs of a pending injury.

The Colorado Rockies are the first major league team to begin testing with Musclesound, a technology that uses ultrasound to measure glycogen levels, the “fuel” inside a muscle. Currently, this test is performed in the trainer’s room, but it is easy to extrapolate how this technology could be embedded into a wearable devices in the near future.


Games are quicker because players are playing faster, right? WRONG: Picking Up the Pace, by Dan Rozenson, Baseball Prospectus

Time between pitches is actually up across the board this year. The exact increase varies depending on the circumstance, but it shows up everywhere. In fact, the average time between pitches is up about 7 percent overall just since the 2011 season. That 1.4-second gap between 2011 and 2015, times 300 pitches per game, adds seven minutes to each game. It’s possible that the tempo of pitcher activity was one of the reasons for the interest in speeding up games, but it sure does not seem to have been affected by the mandate for hitters to stay in the batter’s box between pitches. For whatever reason, the trend of having more time between pitches is continuing. The batter’s box rule doesn’t seem to be the reason for the shorter game durations this year.

First base and third base are the only positions that haven't taken a significant hit in baseball's offensive decline: Adjusting offensive positional expectations, by Steven Martano, Beyond the Box Score

First basemen production has been one of the least affected positions over the course of the last ten years. As is the case across baseball, strikeout rates continue to climb, but isolated power for first basemen is actually higher in 2015 than it was in 2005. Batting average has taken a step back (consequently, so has OBP) but walk rates have hovered around the same level or higher.

First base is an interesting case in a change in demographics. In 2005, established sluggers obtained the most value in weighted runs created. Players like Todd Helton (31 years of age at the time), Carlos Delgado (32), Richie Sexson (30), and Jason Giambi(34) were all in the top ten. This year there are some aging sluggers who continue to rake, players like 32-year-old Miguel Cabrera and 31-year-old Joey Votto, but with the youth resurgence within the game includes heavy hitters such as 25-year-olds Freddie Freeman and Anthony Rizzo, and 27-year-olds Paul Goldschmidt and Brandon Belt.

To put this into perspective, league average hitters at first base right now include Carlos Santana, Albert Pujols and Chris Davis. If we use the 2015 stats for a 2005 player, the closest is Shea Hillenbrand.

More rest for pitchers, fewer injuries for pitchers! But not necessarily less severe injuries for pitchers: Are Six-Man Rotations Ever Worth It?, by Rob Arthur, FiveThirtyEight

I found that there is a strong link between rest and injury rates. Looking at starts on three days of rest, 1.7 percent of pitchers suffered a reported injury within the next two weeks. At four days of rest, the typical amount in the modern age, that number drops precipitously to 1.0 percent. (Maybe that helps explain why the five-man rotation came to be.) Then the injury risk falls even further: at five days of rest — which would be standard for a six-man rotation — just 0.8 percent of pitchers are injured in the next 14 days, for a 20 percent decrease compared with four days of rest. That is a potentially meaningful drop in injury risk.

Despite the drop in injury risk, when injuries were suffered, they were no more severe for pitchers operating on short rest. On either four or five days’ rest, pitchers lost a median of about 21 days of time. So more rest may prevent injuries, but injuries on shorter rest are no worse when they do happen.

Hey, lay off the Mariners, yeah? Trades like the one with Mark Trumbo make sense on some levels: Mark Trumbo and the Relative Value of OBP and SLG, by Dave Cameron, FanGraphs

As a team’s overall OBP goes up, the relative value of SLG goes down, because you don’t need one big hit to drive in a bunch of runs when there’s a decent likelihood of stringing a bunch of smaller hits (or walks) together. And importantly, the inverse is also true; as a team’s OBP goes down, the relative value of SLG goes up, because singles and walks to a bad offensive club are less likely to score runs than a guy hitting a ball over the wall.

In other words, a team of low-OBP sluggers will actually draw a larger benefit than linear weights suggests from adding another low-OBP slugger to the mix than they would adding a high-OBP slap-hitter. If you already have a team that makes a bunch of outs, and you have to choose between two equally valuable hitters — one of whom is a low-OBP/high-SLG guy and the other a high-OBP/low-SLG guy — you’re actually better off with the high SLG guy.

What sort of trends can we see in drafting? Well, more pitchers, and more college picks, to start: Get 'Em Young, Get 'Em Throwing: How Two Recent MLB Draft Trends Can Help Us Anticipate This Year's Results, by Ben Lindbergh, Grantland

During the mid-1980s, which Grantland colleague Rany Jazayerli once called “the Golden Age for college draft picks,” superstars like Barry Bonds, Barry Larkin, and Mark McGwire went to college despite having been prospects in high school. The ’90s were a more productive time for high schoolers, both in terms of quantity and quality. But in the early 2000s, Moneyball helped produce a run on college players that sent the percentage of picks spent on high schoolers to an all-time low — so low, in fact, that the inefficiency flipped. In 2006, Jazayerli wrote, “Now, for perhaps the first time in draft history, a compelling argument can be made that high school players are underrated.” Teams evidently agreed, because a few years later, the percentage of high school picks spiked and kept climbing to its current level, which is as high as it’s been since the ’70s. Rany concluded that “the platonic ideal is about a 50/50 breakdown between college and high school talent,” and that’s essentially where we are today, although because prep players often choose to stay in school, the proportion of signed picks still slants heavily toward college players.