Jayson Werth is on what you might call a forced hiatus from baseball for the moment, but don't expect to see him join any front offices without a philosophy change in how players are evaluated. Baseball has become a more data-driven game, and Werth is fed up with it.
"They've got all these super nerds, as I call them, in the front office that know nothing about baseball, but they like to project numbers and project players," Werth told the Howard Eskin Podcast.
Later on, Werth said that "I think it's killing the game. It's to the point where [they should] just put computers out there. Just put laptops and whathaveyou, just put them out there and let them play. We don't even need to go out there anymore. It's a joke."
Werth is 39, and he played for Mariners' Triple-A affiliate Tacoma earlier this year before saying he was done with it while avoiding the word retirement. His 15-year career was successful by any metric, including winning the 2008 World Series with the Phillies.
"When they come down, these kids from MIT or Stanford or Harvard, wherever they're from, they've never played baseball in their life," Werth said to Eskin. "When they come down to talk about stuff like [the shift], and you say ... should I just bunt it over there? They're like, 'No, don't do that. We don't want you to do that. We want you to hit a homer' ... It's just not baseball to me. We're creating something that's not fun to watch. It's boring. You're turning players into robots. They've taken the human element out of the game, I'm not a fan of the instant replay..."
He then went on to talk about the rule changes that baseball has implemented in recent years.
Werth wasn't terribly efficient throughout his career, but he was undeniably an excellent player. He batted .267 with 229 home runs in his career, also finishing with 300 doubles. He spent most of his playing days with the Phillies and Nationals, so it makes sense he retained some vitriol for the Mets. .
Werth is far from the only one to share this opinion. Statcast MLB stat consumption. Ultimately, however, it's how these stats and analytics are applied that determine their usefulness.to everyday