Hi everyone, I'm Mike Waltieri, Forrester Principal Analyst and your host of Forrester Technopolitics. I'm here at Predictive Analytics World in Chicago, and I'm very happy to be here with Ari Kaplan, president of AriBall, and a Moneyball guy, like a real Moneyball guy. Well, it's great to be here.
Thanks for having me. I've been running AriBall for a number of years and involved in Major League Baseball, like with Moneyball, using information, using analytics. To predict what's going to happen, to put values on players.
So you actually predict, you actually help real teams win ball games. Sure, so I like to say there's above the field and on the field. So above the field is forecasting what's the economic impact of a player and what might they do in future years, and what's the risk involved in putting a dollar on the muscle is the term in the industry. And then there's on the field, which is really exciting.
That you sit with the players, with the coaches, in the clubhouse and use information and analytics and predictive information of behavior to find strengths and weaknesses and habits of the team you're about to face. And so predictive analytics, do you think all of the teams understand the power of this at this point? Sure, so every team's different.
There's all different cultures and all different personalities. And teams are very broad, so there's... Part of the team in terms of ownership, and they're very interested in maximizing their investment, whether it's on the team itself, maximizing the wins, or whether it's the business side.
Do they provide you with all of the data you need to do the analytics? That's a really fun part of it, is where does the data come from? So the teams themselves often collect proprietary information.
They're third-party vendors that collect information. Every single pitch in the majors and minors, you're talking multiple million. About 900,000 pitches in the majors and about five times that amount in the minors. Everything from where the pitcher's hand is when the ball is released, what the spin of the ball is, what the late break movement of the pitch is, where it ends up in the zone.
It sounds like straightforward information, but you can glean really predictive patterns in human behavior. So using information can help detect it. What's changed recently and then you can alert the players and come up with a game plan. So there's third party, there's team information, some teams have entire squads of people recording, for example, where the catcher's glove is set up and then where the pitch ends up to see if the pitch has command of certain pitches and situations like runners on base where they have to change the delivery or not. There's a lot going on now in terms of understanding pitching and hitting, but there's a great future investment.
and collecting large amounts of data in things such as fielding and mechanics of hitting. So, for example, there's sensors, potentially, but right now cameras set up in certain fields, and hopefully all 30 fields in the majors and more in the minors, that collect everything that's happening in the game. So video images, like ball movements and just every movement, that's got to be huge.
Yeah, and the value of that is incredible. So right now it's very subjective to say, you know, Derek Jeter is a better shortstop than Starlin Castro. But you can quantify it by saying how many miles an hour does he throw to first in a key situation?
Is he leaning the right way before the ball is actually hit? So you know what I'm thinking? I'm thinking that the most valuable players on a Major League Baseball team are going to be the data scientist and the computer scientist.
They're going to be some of the most important people on the staff. Absolutely. Ari Kaplan, thank you.
Thank you.