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#TGW: Leader of the (Stat)Pack

The Good Word | by Jon Cooper

There’s no way to predict the future, but Georgia Tech softball is confident it has a pretty good idea of what’s coming when it kicks off its 2019 season-opening weekend at the River City Leadoff, in Jacksonville, Fla., even if they haven’t faced Providence since 2011 (they’re 2-0 all-time), and have never faced UMass-Lowell or host Jacksonville.

They’ll boast that same confidence regardless of who they play all year long.

That confidence is based on the hours of work behind the scenes by head coach Aileen Morales and her staff in creating scouting reports, using sabermetrics, statistical data used to learn tendencies and create a game plan. This isn’t new but has become invaluable to the Yellow Jackets as preparation.

It’s become the same kind of game-changer in softball that it’s been in baseball.

Brooklyn Dodgers owner Branch Rickey is credited with hiring the first statistician in Major League Baseball in 1947. In the late ‘70s, a baseball writer and historian named Bill James created his own series of more complex statistics, which he called sabermetrics. Such advanced stats as wOBA, batting average on balls in play (BABIP), isolated power (ISO), on-base plus slugging plus (OPS+), pitches per plate appearance (P/PA), pitching stats like base runners per nine innings (MB/9), hits per nine innings (H/9), strikeouts per nine innings (K/9), and defensively defensive runs saved (DRS), range factor (RF), and the overall wins above replacement (WAR), have made the standard old-school stats like batting average, runs batted in, wins and earned run average obsolete.

Morales’ exposure to analytics began after reading ‘Moneyball’ by Oakland A’s vice president and general manager Billy Beane. The book and principles contained within confirmed much of her approach to the game.

“I remember reading the book and thinking, ‘Wow! I always thought that on-base percentage was more important than batting average and some of these things. I’m not dumb,’” said Morales, with a laugh. “I got hooked. There are more important stats than just the traditional stats that are being presented to us in a box score.

“When we talk with our team we don’t talk about batting average. My twitter bio says ‘batting avg is dead,’” she added. “To me, weighted on-base average (wOBA) is a way better indicator of how much you produce and that dictates how we structure our batting lineup. It’s very similar to understanding that the player who’s getting on base the most or being most productive needs to be at the top. If you were only going to give me one stat on a hitter or I only got to pick one, weighted on-base average (wOBA) would be the stat that I would ask. It would, at least, give me the best idea of how productive they are in their lineup.”

Morales doesn’t stop at batting average when it comes to bypassing more traditional stats.

“Honestly, I don’t look at RBIs (runs batted in) very much. RBIs are a little bit of a flawed number,” she said. “I think slugging percentage is a better indicator.”

“We had a student manager who was into analytics. We used to dive into statistics and things like that pretty heavily,” agreed assistant coach Reese Mariconda, who starred at Virginia Tech from 2006-09, and traced her used of analytics back to her years as an assistant coach at Fordham (2012-17). “It did a lot for me as far as giving me the knowledge on how to help my team, my hitters, be able to expand on their strengths and kind of be able to have a plan, too, that would fit into what the opponent’s trying to do.

“There are stats that carry more weight with our team,” she continued. “We look at weighted on-base average, extra bases per hit. These aren’t necessarily statistics that you can go look up on the Internet. You have to calculate on your own in certain aspects. On-base plus slugging — OPS, a lot of those, that would be a more team-related statistic, on how is the team or your opponent hitting collectively, like for power, extra bases per hit, how much power are you producing with extra bases. Then, weighted on-base average, how much of a base do you hit for, which, essentially shows me how valuable you are to your team individually.”

Morales and staff split the responsibilities, with pitching coach Alison Owen breaking down Tech’s and opposing pitchers, while Mariconda handles Tech’s and opponents’ hitters. They’ll gather statistics and watch film and create a stat packet. With so many potential statistical categories, prioritizing is crucial.

“You can find a lot of things on the Internet,” said Mariconda, with a laugh. “We’ll look at film on pitchers that we’re going to face, we also have a system that we use called ‘Dartfish,’ that we use to analyze our own hitters and obviously, opponents. We’re analyzing strengths and weaknesses of the opponents and we have certain things that we use on our end that are able to give us an advantage in knowing each of our hitter’s individual strengths, and how each hitter should attack what pitchers are going to throw at them, being able to compile information and examine sequencing of pitches from opposing pitchers and just knowing what they like to do and being able to individualize these plans to essentially allow our hitters to excel in the box and be confident in their approach.”

There is, of course, the risk of too much information.

“It can become an obsession if you’re too reliant on it,” said Mariconda. “Fortunately, as coaches, we’re able to sift through that. We’ll have all the information that we need at hand and then it’s pretty much figuring out what you’re going to feed your team that’s going to be able to help them and not put them into a position where it’s going to handicap them.”

“I think you can (obsess). You’ve got to be very specific about, ‘What is my goal with this information?’” said Morales. “I have this conversation with my staff pretty consistently. ‘If it’s hard for me to understand then it’s going to be even harder for our players to understand.’ So we’ve got to be very precise about what we’re presenting.

“We definitely pick and choose. There are probably some players who probably want to see more stuff than others,” she added. “I think I looked at the game differently as a player. I wanted to know pitcher tendencies, I wanted to know what her strengths were, how her strengths matched up with my strengths as a hitter. When I played our version of analytics without all the spreadsheets, we charted pitchers and kind of had our own very basic version of ‘Okay, these are tendencies. This is what we are looking for.’ I do think at a certain point as a player there can become information overload. You have to feel comfortable. You want to be in that box, have a good plan and then just be in an attack mindset when you’re hitting.”

While sorting through the mounds of information and prioritizing, Morales has found that simply being at Georgia Tech has been advantageous.

“We have some students that helped us automate our scouting reports, our defensive alignments, things like that,” she said. “Being at Georgia Tech, you have so many extremely intelligent students and people you have access to. You can present them an idea and they’re like, ‘Oh, yeah. I can do that,’ and they’re usually able to do that very quickly.’ We’ve gotten in contact with some other people who are doing thesis studies on different sabermetrics and with other people just because, honestly, we’re at Georgia Tech.”

There is nothing more rewarding than seeing the preparation play out. Morales recalled one ACC series last season where analytics paid off handsomely.

“I remember looking at Reese during the game — we were losing at that point — and I said, ‘We’re right where we need to be in this column. We’re going to win. Don’t worry,” she said. “We ended up pulling out that game and pulling out that series win. Had I not known that we needed to be in a certain range, I wouldn’t have known that we were still there and had a chance to win that game. It helped me dictate pitching changes or whether or not I was going to leave my pitcher in. So it’s pretty cool.”

Regardless of analytics’ accuracy, however, there will always still be a human element.

“You still have to have your hunches,” she said. “There’s a time and a place where you have to go with your gut but it’s awesome to have those numbers to back it up — ‘I feel like this is the best match up, this hitter vs. this pitcher.’ That’s gives you that extra confidence.”

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