A look at Driveline Baseball's Velocity Development Program

February 21, 2011 • Training

Traditional baseball conditioning does not make sense, particularly when it comes to pitchers. Pitchers are expected to run long distances and ice their arms after they throw. Many coaches insist that body-weight lunges, push-ups, crunches and plyometrics are the only strength exercises a pitcher will ever need.

The truth of the matter is that this traditional concept of conditioning for baseball is completely backwards. Baseball is a sport composed of brief, explosive physical exertions followed by periods of complete energy recovery. (Triples and inside-the-park homeruns are potential exceptions for complete energy recovery.) Extended cardiovascular training in the form of running poles, getting on a treadmill, or riding a resistance bike, is, for the most part, a complete waste of time if the goal is to get better at baseball.

Baseball is an explosive sport where massive force is created in a very short amount of time. It only makes sense that baseball players should train to be explosive. There's nothing explosive about an extended light jog or crunches. Plyometrics and other body-weight exercises, while including some explosive elements, are limited by the athlete's body weight. There is no room for progression once the athlete adapts to his own body weight.

Throwing a baseball with maximum effort involves just about every major skeletal muscle in the body. This makes it one of the best indicators of a baseball player's explosive strength.

I don't think there's a single coach on the planet that would disagree with what I've said so far, not even Dick Mills who thinks strength training is not only unhelpful but also dangerous.

The thing about explosive strength -- and this may shock some of you -- is that you can improve it by lifting heavy things, like in a weight room.

This is the driving principle behind Driveline Baseball's (Seattle, WA) Velocity Development Program, a comprehensive baseball training program where the main focus is throwing velocity.

Kyle Boddy designed the program and coaches the athletes that are a part of it. The program is split between baseball skill activities, such as defense and mechanics, and strength training.

Regarding the naysayers, Boddy offered, "What they don't get is that training for strength and power also helps young athletes to train general motor patterns, which has a clear translation to all sports. Learning to use hip drive in the back squat, thoracic extension in the front squat, and explosive jumping in the power clean all translate to any sport - you name it, it transfers."

Because throwing a baseball involves so many muscles, the Velocity Development Program is not a program that focuses solely on the arm. As Boddy mentioned, his program utilizes various squat techniques and power cleans, but he also includes deadlifts -- perhaps the best measure of someone's overall brute strength -- and soft-tissue work. He adds, "When they first arrive, they do their self-myofascial release, wrist weight warmups, and resistance band work. The warm-up is pretty fast - it takes about 8 minutes."

The key to the program isn't just getting the athletes to lift the weights, it's to get them to work hard. Not every athlete who walks through the door is ready for the program. They can't all handle it. Boddy says, "We're pretty selective about who we bring in - we're seeking to create a hard-working and competitive atmosphere first and foremost. So we've had to screen out a few guys."

Selecting the right athletes is only part of the equation, though. Working with a coach one-on-one isn't always the best way to stay motivated. This is where the semi-private training model comes in.

Semi-private training, as a basic concept, is like group exercise. A small group of athletes, usually 2-4, train together as a group with a [semi-]personal trainer or coach.

Boddy credits Eric Cressey and Pete Dupuis as having influenced this aspect of his program. He adds, "Semi-private training works better for the athlete and for our business model - we get to train a larger group of guys and fill our facility up, and they get cheaper rates and a better atmosphere to train in. We tend to group them by age first, then skill second, so they have peers they can relate to."

Athletes are competitive by nature, and by throwing a handful of them together as a strength training group this competitive nature helps them push each other to work harder.

Results from Kyle's first Velocity Development Program are already being seen. In one off-season of training, a 15-year-old in his program added 8 MPH to his throws.

Now, if fixing the way baseball athletes are trained were as simple as saying, "Train for explosive strength," I would have said that at the top, and this article would have been very, very short. The truth is that you need a coach that knows how to train for explosive strength.

It's not about getting big (a.k.a. "hyooge") or moving large amounts of weight. It's about becoming explosive and training the correct motor patterns. Exercise selection, volume, intensity, and recovery are all factors that must be taken into consideration no matter how experienced the lifter is.

Kyle's results can do a lot of the talking for me, but I know from experience that Kyle has the knowledge and skillset required to manage these factors. If you live in the Seattle area, I strongly recommend taking a good, hard look at Kyle's program.

You can read more about Driveline Baseball's Velocity Development program here:


What athletes don't know: how to squat

February 7, 2011 • Training

A funny thing happens when you walk into a weight room with an NCAA Division III athlete. It's kind of like witnessing a "Best of Bro-science" compilation, and by "best of" I really mean stuff so awful that you pray for short-term amnesia.

It isn't that what's happening is so aesthetically upsetting that you'd rather watch someone mop up a paint spill with facial tissue. Yes, a lot of it is hard to watch, but what really makes it uncomfortable is that many of them are 100% certain that they know what they're doing.

One of the freshmen said, "I think, by now, everyone pretty much knows how to lift." The irony gave me concussion-like symptoms.

The infamous ball squat.
At least I didn't have to slap anyone for doing this.

During my year coaching NCAA baseball players, I saw countless problems. Among them were some ugly rows, a shocking lack of pull-ups, the improper use of unstable surfaces, and a neglect of soft tissue work. The biggest problem, of course, was -- with the exception of a few athletes -- extremely poor barbell work.

For the most part, if anyone was doing barbell work, he wasn't doing anything but back squats, and calling them "half squats" would have been more accurate. Depth is easily the most prevalent problem with squats.

Poor depth results in quad dominance because of poor activation of the abductors, adductors, hamstrings, and glutes. Because no one wants to back off to a load that their weak posterior chains can handle, poor depth is the toughest problem to correct.

On top of that, poor depth is typically accompanied by excessive ankle dorsiflexion. Instead of bending at the hips, the athlete's knees track forward to allow for more knee flexion. This action moves the barbell closer to the ground, but does not improve the depth of a squat. In this position -- above parallel with ankle dorsiflexion -- the anterior part of the knee faces unnecessary sheer force which may cause pain and may eventually lead to injury.

Next to depth, the most common issue with squats is knee position. Apparently, someone is out there teaching young athletes to squat with a wide stance and feet facing forward. (I have a vague recollection of being taught that myself while in high school.) As the legs bend into the squat and approach 90° of knee flexion, this stance creates unnecessary valgus stress on the medial collateral ligament, which is really good if you're also into grinding your lateral menisci. Such a position suffers many of the same muscle activation problems as poor depth and causes a great deal more pain. (This is true for any flat-footed, standing position where the knees wind up medial to the feet.)

On top of these issues there are chunks of bro-science to deal with: counting that quarter-depth squat as a completed rep so you can tell people "I squatted 400 lbs", coaching cues like "look at the ceiling", and thinking that the Smith Machine is just as good as a barbell.

It takes about 10 minutes to teach someone the correct way to squat, but it takes quite a bit of practice to get it right. Anyone willing to do the work in the first place should be willing to do the work correctly. I'm not going to re-invent the wheel here by breaking the squat down piece by piece and telling you how to do it, but I'm also not going to leave you hanging.

Starting Strength, 2nd Edition, cover.

Mark Rippetoe and Lon Kilgore collaborated on one of the most popular strength training books of all time. It's called Starting Strength. You may have heard of it.

This book is the strength training bible for anyone that hasn't mastered the basic barbell lifts (squat, deadlift, press, clean). It tells you everything you need to know to do these exercises the right way.

If you're serious about strength training, you owe it to yourself to make sure you know what you're doing, and if you're a competitive athlete, there's no reason you shouldn't be serious about strength training.


Measuring pitch variability through PITCHf/x

January 3, 2011 • Analysis

For a while, I've been wondering what can be measured and analyzed using PITCHf/x data that hasn't already been measured and analyzed. A few things crossed my mind, but the most interesting thought was about the degree of variability of a pitcher's pitches.

It would be relatively easy to measure how much variability a pitcher has in velocity and movement if all things were equal. Of course, they aren't.

The two biggest problems for analyzing this type of variability are, as I see them, pitch type identification and park-to-park measurement error. Variability would mean little if half of a pitcher's "two-seam fastballs" are actually change-ups. Variability also runs into problems when parks like Kansas City -- whose radar gun readings are notoriously high -- are included in a data set with other ballparks.

Fortunately, if we only look at a single ballpark -- usually the pitcher's home ballpark because it has the greatest sample size -- park-to-park measurement error should be less of a factor. Without some form of park-to-park normalization, though, interpark comparisons shouldn't necessarily be taken at face value.

Additionally, 2010 saw a huge improvement in pitch type identification. While it still isn't 100% accurate, it is close enough on many pitchers to give me confidence while playing around with my ideas.

I haven't really dug into the numbers yet, but I will be looking to see if variability within a pitch type helps or hurts a pitcher. My gut feeling is that the number itself won't have much meaning.

To calculate the variability, I plan to capture the 95% window using two measurements of the standard deviation in both directions from the mean. By definition, this eliminates the outliers, but it will take some study to determine if that's really the measurement to use.

It may be beneficial to use a pythagorrean measure to find the variability for pitch movement; however, this would not appropriately model pitches that have greater variability vertically than horizontally (and vice versa, of course).

Look for a follow-up after I play around with this idea.


Thinking about run values

December 30, 2010 • Analysis

For some time, I've been looking for a way to appropriately integrate run values into the PITCHf/x database. I have read articles at Beyond the Boxscore, Inside The Book, and Cubs f/x, but I am no closer to getting what I want. Unfortunately, I lack the resources and time to find the answers myself.

Many tables have been published with run expectancies for the 12 ball/strike count states for various time periods. Tables have also been published for the 24 base/out states. Because the two tables contain different representations of the same data, there's no way to combine them. What I would like to see -- and I'm sure this makes me a sadist -- is a run expectancy table for the 288 ball/strike/base/out states.

Yes, that's one hell of a matrix to process, but there are two thoughts that seem to be the beginning of arguments against the two relatively simple approaches:

  • The thought against only using the 12 ball/strike count states table: a first-pitch strike in a bases loaded, no out situation has to effect the run expectancy more than a first-pitch strike in a bases empty, two out situation, right?
  • The thought against only using the 24 base/out states table: an 0-2 single with a runner on first base has to effect the run expectancy more than an 3-0 single with a runner on first base, right?

Admittedly, I don't have the knowledge or skills necessary to issue either of those thoughts as facts, so I have posed them as questions. It seems logical, though, doesn't it?

I think an appropriate time period for the analysis to cover is 1998-present -- since the last expansion.

Does anyone know if anyone has tackled this subject, successfully or otherwise? Is this covered in a book that I have not yet read -- possibly even one that I have read?

Consider this an open call for help in this matter.

[UPDATE: Tom Tango finally calculated the 288 states after the 2018 season, but his website was not working when I tried to grab the link.]


2010 Texas Rangers Win-Curve Revisited

December 28, 2010 • Analysis

In 2009, I published a win-curve that predicted Texas Rangers attendance for a given win level. The Rangers won 87 games, and my win-curve predicted 27,958 attendees per game for that win level. Actual attendance was only 27,641. The difference was 317, only a 1.15% difference.

This season, I updated my data and published another win-curve. The yellow dot on the graph marks the 2009 attendance level, and the red dot marks the 2009 win level.

Texas Rangers, Wins vs Estimated Attendance, 2010
2010 Attendance Prediction. For a full description, read the original article (link above).

In 2010, the Texas Rangers won 90 games. My win-curve predicted an average home attendance of 31,202. According to ESPN's numbers, the actual average home attendance was 30,928.

The difference of 274 attendees per game translates to only a 0.89% overshoot. The model was more accurate this year than last year.

As the season approaches, I will update the data and issue a new prediction.