San Francisco Giants: It’s Time to Embrace (some) Analytics

LOS ANGELES, CA - AUGUST 13: Madison Bumgarner #40 of the San Francisco Giants pitches during the third inning against the Los Angeles Dodgers during the first inning at Dodger Stadium on August 13, 2018 in Los Angeles, California. (Photo by Harry How/Getty Images)
LOS ANGELES, CA - AUGUST 13: Madison Bumgarner #40 of the San Francisco Giants pitches during the third inning against the Los Angeles Dodgers during the first inning at Dodger Stadium on August 13, 2018 in Los Angeles, California. (Photo by Harry How/Getty Images) /

The San Francisco Giants can really change the direction of their franchise in the next few weeks, and after watching the successes of certain teams the last two seasons, it’s clear they need to embrace an analytics bent.

John F. Kennedy once said, “Change is the law of life and those who look only to the past or present are certain to miss the future.” The San Francisco Giants have missed the present in MLB because for the last three years they’ve only been looking to their past success to realize that the game has adapted and evolved beyond that. An embrace and integration of analytics is the only thing that can help the Giants compete in 2019.

Let me be clear right away, I’m not embracing a full “Oakland A’s, Tampa Bay Rays” style of analytical embrace. Far too radical, and frankly the Dodgers are on the fringe of being to radical. Yes, for the A’s and Rays it worked to rack up 90+ wins in the regular season. However, in postseason practice, it was never going to work, and it arguably will never work. Relying on analytics on a situation by situation basis to make decisions for you hasn’t resulted in a championship.

Three teams in recent years have used analytics in a way to help boost the baseline performances of their players, in turn making them successful. The Red Sox did it with plate approach, the Dodgers did it with rebuilding swings, and the Astros did it with spin-rate and rebuilding Gerrit Cole and Justin Verlander. So could they borrow from all three? And how could they?

The Red Sox don’t preach a whole lot of “launch angle” type stuff. Have they rebuilt some swings to be more optimal for offense? Sure. But the Red Sox just go up to the plate and try and hit the ball as hard as they can. Their analytics lean towards making the most optimal contact. The Giants plate approach?

Well nobody knows if they even had one at any point this season. If they did, they didn’t stick to it, or just flat out ignored it. Again, the Giants should be embracing an analytical approach similar to that of the Red Sox for plate approach. But what about how the Dodgers have rebuilt some swings?

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Justin Turner stands out for what he was able to do the last two or three years at the plate with his own swing rebuild. You can also throw in Max Muncy, who hit 35 homers just two years removed from being a cast-off on a terrible A’s team. Since there isn’t a positive test on record for him yet (jokes), you probably should thank analytics for his rebirth.

Building the swings of Cody Bellinger, Muncy, Turner and Chris Taylor in recent years has helped the Dodgers become who they are. I can just imagine the Giants working Joe Panik, Brandon Crawford, and even Austin Slater or Chris Shaw’s swings to be more optimal for consistent hard contact.

One of the more interesting things the Giants can do is embrace the Astros approach to pitchers and spin rate. Take a look at the rebuild of Justin Verlander and Gerrit Cole, Verlander especially. Verlander’s average fastball velocity dipped under 95 MPH in 2013, and didn’t return until last year, especially with the Astros. In 2017 it reached his highest average since the 2012 season, and his 2018 average fastball velocity was better than that 2012 season as well. Throw in the fact that people swung and missed on Verlanders pitches this year more than any other in his career, it shows the Astros are doing something right with their look at spin-rate.

Madison Bumgarner’s fastball velocity has gone down since 2015, where it was at its highest of 93.1. Last year it was down at 91.4 which was the same as his 2017 average velocity. Can you imagine Bugarner adding velocity back? Can you imagine him inducing more swings and misses with an increased spin-rate? Can you imagine a few others in that staff improving at that level? Same with Jeff Samardzija?

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Ultimately, the Giants are a talented team. But, they haven’t been able to overcome some of their weaknesses in recent years. The Astros, Dodgers and Red-Sox help attack their own weaknesses by implementing analytics to help boost their floor. T

he Giants should start to do that. The revival of Max Muncy, Justin Verlander, and even J.D. Martinez’s success with the Red Sox should show the Giants a path to success with analytics, while not being overboard with numbers in situational setups. When it comes to player development however, it’s exactly the right approach.

And again, I’m not advocating for the Giants to fully embrace the use of analytics in a situational sense. That’s where you get Dave Roberts’ level decisions. Either that or he has the worst managerial feel I’ve seen in a contending manager. Take a look at how Cora managed. He went with the best he had available.

He made some ballsy decisions like starting Kinsler instead of Benintendi, like his use of certain bullpen guys early then riding out David Price in the ALDS, but ultimately we’ve seen that with the Giants before.


I don’t want to see them turn to that Rays or Oakland A’s level of situational management. But to embrace analytics in a player development sense, the Giants could get a lot more bang for their buck in-house if they did.

If the Giants have any hope of competing in the near future, they’re going to have to get there with the help of analytics. Their past successes can’t come at the same way they did in 2010. They need to adapt to where baseball has gone, and is going. They’re presented with a grand opportunity to do that this offseason, and they better not swing and miss.