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How an understanding of advanced statistics has increased my appreciation of baseball

And how it can increase yours, too

MLB: Philadelphia Phillies at Miami Marlins Jasen Vinlove-USA TODAY Sports

This weekend, baseball writers and other amateur sabermetricians were sent into outrage when Joel Sherman of the New York Post published his column, describing how advanced statistics were killing the game of baseball. “Pooh-pooh[ing]” the basics like pitcher wins and RBI’s has created a detrimental disconnect between generations of baseball fans, Sherman claims.

My Mom sent me the article in a text message on Sunday morning. Just like I think people do with my articles, initially I read the headline and scoffed. Then I read the article, and simmered over football, and then read the article again.

Sherman isn’t slandering the Pantheon of Sabermetrics built by Bill James and Billy Beane. There are some fair and decent arguments. He’s made the necessary concession that advanced statistics are necessary for teams to glean the most information from their players, and with that I obviously agree.

With that said, I think that advanced statistics can open a fan’s eyes to different nuances of baseball that would increase said fan’s appreciation of the game.

Like anything else in this world, learning about sabermetrics in baseball does not come without research and reading on one’s own time. Without taking the step of actually learning about concepts and their weird abbreviations, it’s almost a default to shrug them off and say “Hey, I’m doing just fine with batting average.”

But in reality it doesn’t take that much effort to invest your fandom with a better knowledge of stats. Thanks to one book—Smart Baseball by Keith Law—and a casual readership on sites like Fangraphs, Baseball Prospectus, and others, I now tout both my knowledge and appreciation of baseball on this site.

So I just wanted to share a couple of my own reflections on how advanced statistics has affected my view of baseball, along with some courteous rebuttals to Mr. Sherman. Hopefully you’ll be able to see where I’m coming from.

Better appreciating your favorite team’s players

It used to be that even if your team was out of it, you could still be engaged daily by a favorite player pursuing a milestone—20 wins, 100 runs, 100 RBIs, etc.

I can remember my father, a lifelong Yankees fan, happy on the final day of the 1997 season that Bernie Williams hit a solo homer to reach exactly 100 RBIs. My dad felt he had taken both the career-long and season-long journey to accomplishment with a player he liked.

Perhaps no one can appreciate an individual player’s contribution to a team like Marlins fans. When your home team fails to reach the playoffs in the last 15 years, all you have is the players to root for.

Just last year, Giancarlo Stanton won the National League MVP Award, as the Marlins recorded their eighth consecutive sub-.500 season. The centerpiece of Stanton’s season was a 59 home run onslaught that for the first time since the Steroid Age, dug up names like Roger Maris, Mark McGwire, and Sammy Sosa.

Sherman writes that fans of old yearn for the days when people rooted for players to reach statistical thresholds divisible by five. Today’s fans don’t instantly appreciate the slugger who swats 40-50 bombs, allegedly.

But sure enough, if you check our archives, you’ll see that everyone in Marlins Nation—from guys like me, to the not-so-sabermetrically-adept—were bent on Stanton hitting 60 home runs. That sentiment that Sherman believes is missing from baseball today actually hasn’t gone anywhere.

What happens when your team trades that player, as well as all of the other sluggers on the roster? When your team is missing that quintessential slugger?

Advanced statistics can help the average fan gain a better appreciation for what they have on a team.

J.T. Realmuto, one of the brightest spots in the Marlins lineup, is a perfect example. A younger me might have pulled his baseball card out of a pack, seen his pedestrian .282 batting average this year, and thrown it on the bottom of the pile.

But what if I take a step further and say “You know what, I’m ok with a walk being as good as a hit” and I look at on-base percentage. Then I see that Realmuto’s OBP is way above-average (actually four points higher than Stanton’s this year). That resonates with me as both an evaluator and a fan, and it should do the same for any fan. After seeing Realmuto’s .845 OPS, maybe I put that Realmuto card in a sleeve on my shelf.

If I’ve taken the time to further my knowledge of the game even more, I go to wOBA and wRC+, and I see that with a 131 wRC+ this year. Realmuto is hitting 31% better than the average hitter (that’s how easy it is to understand Weighted Runs Created Plus—the amount above or below 100 is the percentage better or worse than average a player is creating runs). That gives me the best picture of how good he has been this year.

Am I rooting for him to hit some square wRC+ number like 140 or 150? Not necessarily. But I do compare his wRC+ to previous years, and I see that Realmuto has improved his run creation by 24% over last year. Despite his “conventional metrics” being more middle of the road, I have a new, legitimate reason to be optimistic about the Marlins.

Earlier this year, when J.T. Realmuto broke the 20-home run plateau for the first time in his career, fans were excited. If J.T. somehow knocks in 29 RBI’s in the next two weeks, though it might not be statistically noteworthy, it will also be exciting.

These two mindsets don’t need to be mutually exclusive.

“How can you not be romantic about baseball?”

Expected statistics have become public enemy number one to conventional baseball fans. The arguments have been made repeatedly. Jayson Werth made the news after retiring when he gave his famous “Just put the computers out there” diatribe.

Sherman directly called out an expected statistic here:

Is anyone tracking if their favorite has exceed five wins above replacement or if their most beloved pitcher had an xFIP that has dropped below 3.00?

I get it. If people can compute to a certain statistical probability that a certain event is likely to occur, why even watch the game?

In my opinion, this is the glass half empty argument. Conventional baseball fans hunger for the reintegration of the human element into baseball. “Clutch isn’t dead, and hustle and grit matter.” They’re told that technology is threatening that.

But contrary to popular belief, I think advanced statistics embrace the human element more than anything else. You just have to know about what to look at to see the glass half full.

When people ask me what my favorite baseball moment of all time is, I tell them it’s Game 7 of the 2016 World Series. In the bottom of the eighth inning, Aroldis Chapman was inserted for his fifth appearance of the series. The Cubs led by two. After two quick outs and a hit, Rajai Davis stepped up to the plate.

MLB: World Series-Chicago Cubs at Cleveland Indians Tommy Gilligan-USA TODAY Sports

It felt like Davis would be overmatched by the All-Star closer, and the advanced statistics backed that up.

In 2016, Rajai Davis had an Expected Slugging Percentage (xSLG) and Expected wOBA of .339 and .278 respectively. Both of those were bad enough to fall into the bottom 7% of the league. Davis’ lacking power figures probably weren’t helped by the fact that he was called upon to face Chapman with the game on the line.

Brandon Guyer was on second base at the time. With a two-out double, he raised the Indians winning chances from a measly 5.1% to a marginally better 12%. Still, the game seemed to be in hand for the Cubs with Davis coming to the dish. Baseball Prospectus’ Run Expectancy tells us that in 2016, with a man on second and two outs, teams had just a 31.7% chance to score one run.

With all 5’10” of Rajai Davis choked up to the barrel against the flame-throwing Chapman, we see that the odds of him and the Indians coming out on top in this situation are slim-to-none, and Slim just took the train.

Computers can anticipate the outcome, but play no role in deciding it. Let’s leave that up to the players:

Brad Pitt’s iteration of Billy Beane said it best in Moneyball: “How can you not be romantic about baseball?” If baseball’s statistical revolution has taught me anything, it’s that you can line the dominoes up as tight as you can, and you still won’t know how they’ll fall.

Cleveland went on to lose that night in one of baseball’s wildest Game 7s, but Davis home run put them back in the fight, raising their win expectancy at the time from 12% all the way to 52.5%. Although the concept of “clutch” has commonly been debunked sabermetric circles, moments like these constructively prove that it’s still out there somewhere.

Waiting for moments like these make me appreciate the game of baseball. Joel Sherman was right when he said this:

Baseball is novelistic, you turn the pages daily and the rewards are generally at the end of a long, challenging commitment.

But said rewards don’t necessarily have to be cumulative rewards. A good novel has a good ending, but a really good novel has a good beginning and middle as well. Fifty home runs is always fun, but an above-average on-base percentage or a low FIP aren’t bad either. Watching your 25th man hit a walk-off in the dog days of the season is pretty cool, too.

If you’re a member of the next generation, and you believe at first glance that advanced statistics are killing the game of baseball, I’d implore you to try reading up on them before completely rebuking them.

Statistics courtesy of Fangraphs, Baseball Reference, Baseball Savant, Baseball Prospectus, and