Batters actually hold a decent level of influence on their BABIP, which is something that not a lot of people realize. Because there are different types of hitters (mainly speed, power, and contact hitters), not everyone should be expected to have the same “30% outcome” for balls in play. The main source of this influence comes from what is known as a player’s “batted ball profile,” which consists of the following stats:
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Home runs (HR): The argument for this one is pretty simple. The best possible thing a hitter can do in any given at-bat is hit a home run. No matter what. You can't name a single offensive circumstance where something else would help the team more than a home run. My disdain for hearing "we don't need a home run" is a topic for a different day. Still, even the leaders in home run totals each year generally hit a home run around 5 to 10 percent of the time. So if you only focus on homers and ignore everything else, the odds of coming up with the best overall offensive player probably aren't great. - Snyder
The last notable disadvantage of OBP is that it is not park or league adjusted. It is easier for players to post a higher OBP in parks such as Fenway Park or Coors Field than the Oakland Coliseum or Petco Park. Likewise, OBP has fluctuated throughout time. Carl Yastrzemski led the American League with an OBP of .395 in 1965. However, in 2001, Jason Giambi put up the highest mark at .477. There are ways to adjust numbers for park and league context, but we'll save that topic for a later date.
You just need to look at some of the players hitting between .280 and .285 to see the validity in Correa's point: Boston Red Sox second baseman Dustin Pedroia, Cardinals third baseman Matt Carpenter, Cincinnati Reds third baseman Todd Frazier, San Francisco Giants right fielder Hunter Pence, Milwaukee Brewers center fielder Carlos Gomez and Baltimore Orioles center fielder Adam Jones qualify for the new .300. Every one of them was an All-Star this year.
First compare the names on the left to the ones on the right. Notice anything? With the exception of Buster Posey, did you draft any player from the left side before any player on the right? OK there is Dexter Fowler, but there are always a few exceptions with any example. The players on the right are the superior players, Matt Carpenter included. While he didn’t live up to expectations, Carpenter did score 99 runs. The only players to score more runs from either list all come from the right side, Bautista and Trout. Denard Span was 10th in the league in scoring runs (like I said, an exception to every rule) but the next highest player from the left side is Howie Kendrick down at #30. Everyone else on the left had 81 or fewer runs scored where everyone on the right scored more than 81 times except Hanley and Fowler (who both had under 450 at bats due to injuries).
Now that we’ve covered slash line statistics and plate discipline numbers, all that’s left to go over is batted ball data. The most common batted ball stat that is used is batting average on balls in play, or BABIP for short. While a typical batting average tells you how often a player gets a hit in general, this batting average determines how often a player ends up getting a hit when they hit the ball within the field of play. It is calculated by subtracting home runs from totals hits and dividing that by at bats minus strikeouts minus home runs plus sacrifice flies, which translates to the following formula:
As the hitter has recognized pitch height, they will then use the separation between their pelvis and shoulders and much like a rubber band, “snap” into a violent rotation of their body. This immediate energy creation will transfer up the body and into the arms and hands which will then allow the barrel to flail or turn around the hands and knob. Whatever the hitter’s top barrel speed is, the goal should always be to get there as soon as possible. Just like a sprinter off the blocks, gaining top speed in the shortest amount of time is crucial to facing faster pitching.
The conclusion of the GIIB article shows that team gOBP has a correlation coefficient of 0.95 with R/G, a slight but meaningful improvement over the correlation coefficient of 0.93 between team OBP and R/G. This first test is straightforward: using Retrosheet, I collected team R/G, OBP, and gOBP for all 1,482 team seasons dating back to 1955. I then fit a linear model to these data and computed the correlation coefficients for each pairing. The results are below.
Traditionally, players with the best on-base percentages bat as leadoff hitter, unless they are power hitters, who traditionally bat slightly lower in the batting order. The league average for on-base percentage in Major League Baseball has varied considerably over time; at its peak in the late 1990s, it was around .340, whereas it was typically .300 during the dead-ball era. On-base percentage can also vary quite considerably from player to player. The record for the highest career OBP by a hitter, based on over 3000 plate appearances, is .482 by Ted Williams. The lowest is by Bill Bergen, who had an OBP of .194.
OBP has become synonymous with the book “Moneyball” because at in the early 2000s, teams weren’t properly valuing players with high OBPs and the Oakland A’s could swipe talented players for cheap because they were one of the few teams paying attention to walk rate. These days, every team has come to accept how vitally important OBP is to their success, and that particular “market inefficiency” has been closed.
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Prior to 2010 we only listed the top 100 and monitored those who made and slipped off the list. Here is that original fast fact preserved and now useless due to the list including 1000 names: Modern superstars are making the list as they meet the one-thousand minimum games played threshold: In 2001 Jeff Cirillo & Manny Ramirez met the requirements and joined the top one-hundred. In 2002 Cirillo slipped off the chart and Jason Giambi made it while Chipper Jones & Alex Rodriguez missed the cutoff by less than 2/1000 of a point. In 2003 Jason Giambi slipped off the chart, Chipper Jones just missed it once again (his career average is .30870), and Vladimir Guerrero vaulted onto the list at forty-first — higher than any other active player, that is until 2004 when Todd Helton launched into the top 20 all-time.
It's easy for me here if I'm judging a player or team in any given season, because OBP is essentially measuring the amount of times a player doesn't make an out. If no one ever makes an out, I'm pretty sure the team would find a way to do just fine on the scoreboard, right? As for judging players in a historical context, I'll go with OPS+ because it lumps in on-base ability with power and adjusts for all eras, from the steroid era to dead-ball era and everything in between.
Here are our nine candidates for best primary offensive stat -- and please note that every offensive stat here is very important, we're just trying to pick which is the top dog. Also note, categories such as doubles, triples and stolen bases are clearly important but couldn't be rationally argued as the most important stat. Thus, they were left out. - Matt Snyder
I am in a 14 team league with average and OPS, wish it was OPS and OBP. I had Dozier in that league, the year before I had Altuve and Dozier. I went after SanDiego’s Cabrera what a mistake. Hope to have Altuve and Dozier this year but for value Altuve looks to be a early 2nd round pick, that is to high for me, I would rather get a guy with power and RBI’s in the first two rounds.
Have you ever wanted to learn more about the game's newer and more advanced statistics but didn't know where to start? Have you ever read an article that liberally mentions WAR or xFIP, leaving you feeling as if you walked into Math 401 when you haven't taken Math 101? It's ok, don't worry; that's how we all felt the first time we stumbled upon these figures. The good news is that the best of these statistics make a great deal of sense once they are explained. Often, though certainly not always, the calculation of these figures is straightforward upon closer inspection.
Brian Dozier is another low average players the batting average purists love to hate. He hit .242, but the rest of his numbers were superior to most players at second. We complained about his average but nobody took into account that he walked 89 times and scored 112 runs. If you’re going to count all those extra runs he scored because of the walks you should count the walks as well, and that’s something batting average doesn’t do. While looking for a comparable player to Dozier, one interesting names came up. Look at these two batting lines.
These types of movements encourage poor technique and motor patterns. I have talked about the central nervous systems relationship with movement patterns in the past with speed development and in baseball youth athletes, the same rules apply here. This type of training negatively affects your body’s motor/muscle recruitment patterns during a game setting.
Staying connected to the body's rotational energy starts when the hitter steps into the batter's box to prepare the launch position. To acquire a powerful launch position, the batter's upper body and shoulders must rotate to a fully loaded position. An inward turn of the upper torso and shoulders stretches the muscles of the upper body and pelvic region. Some refer to this as loading. With good transfer mechanics, the contraction of these muscles combined with the energy of hip rotation is converted into angular acceleration of the bat-head. The video below shows, and discusses, a powerful launch position.
the reason i think XBH is the perfect stat is for the same reason you dismissed it, because it does not consider HRs more important than doubles and triples… One problem with the traditional 5×5 is that we count HRs 3 times, Power is not the only important stat… and using XBH gives speed guys a little more value because now they can contribute well in the same amount of categories a power hitter can…
Slugging percentage (SLG): Compared to most of the other "old" statistics, slugging is beautiful in its simplicity -- it's simply total bases divided by at-bats, and gives us a nice snapshot of a player's power. Think about it, with batting average you have to factor in fielder's choices, errors and walks and the such, while slugging is easy (although, it is a derivative of batting average, as you need at-bats instead of plate appearances). It also passes my test for a useful stat -- immediate understanding of what it means when you glance at the number. - Rosecrans