08
09
2018

Data-Driven on a Budget: Baseball Analytics for High Schools and Colleges

The Analytics Age has come to baseball and it is not going away. While the price of very accurate tracking technology has come down and the ease of use has increased, coaches outside of the professional level still struggle with both the learning curve for new technology and the constraints placed upon them by budget and time.

Most coaches that reach out to us have (to borrow a phrase from Sam Walton) “too little time, too little money and two little kids.”

So layering in the expectation of learning new technology is not high on the priority list. But increasingly functional deployment of technology will be a requirement to win games at the amateur level.

It’s the responsibility of both Driveline Baseball, as proponents of using data to make player development decisions, and technology makers, as sellers of products to coaches, to keep those limitations in mind and design around them…not shame hard-working coaches because they aren’t “cutting edge”.

What’s Reasonable – A Test for Tracking Technology Decisions

It’s not reasonable to expect the pitching coach at a D3 school who teaches middle school to make ends meet is going to be the foremost expert on ball flight physics.

However, it is reasonable to expect that coach to be committed to helping find and develop the best players. Increasingly, part of that job is using technology to augment your coaching abilities.

The goal for a small school should be to get the absolute most out of the technology they have available. If you feel confident you are doing that, then it’s the time to layer on new technology.

Key Component: A Data Collection (and Review) Process

The key to using any type of technology (barbells, Rapsodo, Motus, whatever) is to have a process for recording and reviewing the data.

The good news is that you already do this in an informal way. Checking in with the guys during stretch, logging weight room work, charting bullpens, this is all data collection.

While the process we use internally has significantly more bells and whistles on the technology front, the basics of the process are replicable from Little League to the big leagues.

  1. Initial Baseline. You need to know where your athletes are at. How complex and detailed this is depends on what tools you have. However, you can’t create a training plan in a vacuum so having some semblance of who you are dealing with is critical. Here is what to look for at a high level:
    1. Pitchers: velocity, control, strength/power, mobility/joint stability.
    2. Hitters: exit velocity, ability to hit off-speed, strength/power, mobility/joint stability.
  2. Training Intervention. Intervention is a scary word but it’s anything you do to make a guy better: weight room, team practice, rest. I’d block out 4-8 weeks to make sure the intervention is having an effect.
  3. Retest. Is the training working? Let’s go find out. If you put an athlete on a strength-focus, did their strength improve? Any carry-over to their pitching velocity or in-game power?

Getting the Most Out of Small Budgets

The key to managing a data-driven development program is simply setting up tracking, review and retest protocols for any technology you deploy.

 

Below are tiers of technology that you can deploy for no, low, and medium cost.

By way of example, a simple protocol for testing throwing velocity is measuring mound velocity or long toss distance and then retesting each month or two. Alternatively, having athletes fill out a short questionnaire before practice measuring well-being can be easily aggregated inside a Google Form or something similar.

Simple protocols work best for all of the Tier 1 groupings.

Tier 1 – Readily Available, Mostly Free

Schools should look to get the most out of these resources first. This is the lowest-hanging fruit and you can significantly improve on-field performance at basically no cost.

  • Barbells – available for free in most school weight rooms.
  • Bats and Baseballs – a sunk cost for most baseball programs.
  • Athletic Trainers – if available at your school, they are typically part of the overall budget.
  • Athlete Well-Being – you already ask guys how they are doing, write it down.

Tier 2 – Small to Medium Investment

These can be applied in stages, one per year. Or, with a dialed in process for collecting data, you can do a big fundraiser to scrape together the $10,000-$15,000 it will take to purchase this all at once.

  • Rapsodo Pitching – a complete tool for pitch analysis at scale for teams.
  • Batted Ball Flight Trackers – Hittrax and Rapsodo are probably the leaders here. There are others at different price points.
  • Motus – workload management for pitchers.
  • Barbell Speed Trackers – tracking barbell speed gives you the opportunity to get better insights into force and power.
  • High-Speed Cameras – high-speed video allows you to marry “feel” data from players to “truth” data from Rapsodo.
    • Edgertronic – the top-of-the-line. Gives you ball flight, finger pressure and spin stabilization.
    • Sony A1000 – the best mid-tier option. Less resolution on fine details but you can roughly see grip.
    • iPhone slo-mo – mileage may vary.

Tier 3 – Only if donated

This includes a ton of big-ticket items like installed motion-capture systems and the like that are just not in the price range for small schools. No matter the data quality or granularity they aren’t likely to happen for you unless an athlete’s mom runs a hedge fund.

Unexplored Opportunities – Clubs on Campus

Tracking all of this data takes time.

And time is limited–both explicitly by the NCAA and by the sheer volume of tasks most coaches have to take on just to keep programs afloat and at-budget.

However, there are 2-3 students at your school right now who are:

  1. Analytically-minded
  2. Willing to work for free
  3. Love baseball

Those students can all be found in your school’s computer science/math/economics clubs.

There is actually a much bigger opportunity that small schools have that they don’t often take advantage of.

Inside of the analytics community, most of the publicly available datasets have been strip-mined. There just aren’t many more insights to be gleaned from the 2014-2016 PitchF/X database about how to value pitchers.

However, player development analytics is basically wide open. The catch is that no MLB team is going to make sensitive player data available to the public. So the talented analytics people, those who aspire to the MLB analytics jobs of the future, don’t have a lot to work with.

But you can give them that opportunity. And, to a smart computer science kid, a well-analyzed couple of seasons of player data, even from a smaller school, is worth a lot to burnish their portfolio for MLB internships.

And the insights will help you win games. It’s a win-win that is very much underutilized.

The investment of a couple of hours emailing clubs and giving short presentations at club meetings could yield 1-4 years of quality analytics work at the cost of a couple of team shirts and a weekly meeting.

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