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.
To do this drill, you stride over the outside stick, and while completing the swing, work on getting the back foot over the back stick, really focusing on weight transfer. Note how in the pictures, she has stepped past the stick and to the tee, and in the next frame, began shifting her weight from her back leg to the ball. This drill is excellent for weight transfer and using the lower half to drive the ball.
By keeping it BA over OBP, you keep more players valuable in fantasy and there is much more strategy because the knowledge of starting a guy like adam Dunn might help you in the power categories, but it will hurt you elsewhere… or if you start a BA guy it will help you in BA but might hurt you elsewhere… BA calls for more balance and more strategy, and i am a fan of that(thats where my preference comes in)…
Recall that we can use the batter's OBP, the pitcher's OBP, and the league OBP to find an expected OBP for a given matchup using the odds ratio. Since gOBP is still a proportion, we can use it to perform the same analysis. To determine which is more accurate, we first group the batters and pitchers into bins with width five points (.005). We then find an expected OBP for all pitchers and batters in that bin, and compare this to the actual results of those matchups. As an example, consider the first pair in our database: David Aardsma and Bobby Abreu, who faced each other once in 2010.
Offensive wins above replacement (oWAR): I like it because it removes the problematic portion of WAR, which is its defensive estimates. oWAR is all about contributions made at the plate and on the bases, and it measures those quite well. It's denominated in theoretical runs tied to "replacement level," which approximates the productivity of a "freely available" sort of player (e.g., the bench player, the minor-league veteran, the waiver claim). Batting, base-running and an adjustment for positional difficulty are all baked in. - Perry
Every baseball player would love to be able to hit for power, but not every baseball player is a natural like Bryce Harper. There are a lot of things that go into a powerful baseball swing, and no one swing method or form is the right fit for all hitters. However, there are some "Cream and Clear"-free ways that can help all players add power. With the strategy and preparation, you can develop both your mind and body for power hitting as well as improve your form regardless of your preferred stance or swing.
Here's how to practice the proper weight shift going back. Set up with your driver, but take a narrow stance, about 12 inches wide. Then make a slow-motion swing, stepping out with your right foot as you start the club away (above). This side step will get your weight shifting to the right. With your weight in your right instep, you're in position to drive your body toward the target as you swing down. That's how you hit the ball with power.
Comparing a baseball or softball swing to a car engine is something that I do almost everyday. It’s an easy way to help kids and parents understand how the system inside the swing works. For someone who doesn’t look at hundreds of swings a day, it can be difficult to identify or help a player become a more efficient swinger of the bat. A lot of times coaches will see a result like a pop up or ground ball and associate the weak contact with lack of effort. Most of the time, this is simply not the case. In the following article I hope to help players understand the importance of not making “early mistakes” and also help coaches and parents break down the efficient swing. To do so, we will break the swing down into three phases. The three phases are 1. Acceleration/Angle Creation, 2. Maintain, 3. Release. They are illustrated in the picture below in a Playoff home run by Francisco Lindor.
In Phase 2, the hitter may continue to accelerate but hopefully has already reached top speed. They will maintain top speed as they continue to rotate their hips and shoulders. Contact can be made in Phase 2 before Phase 3 is ever needed. This is demonstrated when players like Mike Trout will maintain bent arms well past contact on inside pitches. If Phase 1 and Phase 2 are executed at a high level, theoretically Phase 3 is not needed.
Don't swing down on the ball. The backspin you gain from doing so does not outweigh the exit velocity loss that occurs as a result. The best way to get distance is to swing up through the ball. If you slightly undercut the ball that way, you get backspin while achieving a better launch angle and maintaining as much exit velocity as possible. Advanced analytics show that the most effective way to hit home runs is to swing with an attack angle that's slightly less than the ideal launch angle. The following article explains this in more depth.
Henry Chadwick, an English statistician raised on cricket, was an influential figure in the early history of baseball. In the late 19th century he adapted the concept behind the cricket batting average to devise a similar statistic for baseball. Rather than simply copy cricket's formulation of runs scored divided by outs, he realized that hits divided by at bats would provide a better measure of individual batting ability. This is because while in cricket, scoring runs is almost entirely dependent on one's own batting skill, in baseball it is largely dependent on having other good hitters on one's team. Chadwick noted that hits are independent of teammates' skills, so used this as the basis for the baseball batting average. His reason for using at bats rather than outs is less obvious, but it leads to the intuitive idea of the batting average being a percentage reflecting how often a batter gets on base, whereas in contrary, hits divided by outs is not as simple to interpret in real terms.