My problem with analytics is that it has gotten to a point where they are interpreted from a perspective of being the gospel rather than one piece of good information. Analytics and sabermetrics are great tools for modern baseball, but not everything in the game can be quantified scientifically, at least not perfectly. There are just too many variables. Even analytics are constantly changing and evolving, WAR already looks outdated rather than the revolutionary tool it looked like 10 years ago. So clearly, even more modern analytics aren't perfect. Is ERA a great stat? Nah, it's not, but to say it is useful only after 500 innings goes far beyond a reasonable scope for using it. Small samples are often overused to a great fault of misinformation but this is the other extreme end of the spectrum. Josh Hader has 200 career innings, it would take him about 7-8 years of an injury free career to have a "useable" ERA, this is more than many relievers will pitch professionally in their entire career. While there are better ways of measuring pitching performance and predicting future outcomes, there's clearly a correlation between lower ERA and better pitching performance. Corbin Burnes had a 2.61 ERA last year and is at 8.81 this year -- that alone doesn't illustrate why he was so much better last season, but it's not a coincidence that it was much lower in 2018 when pitching much better. Yes, there are exceptions to the rule, but generally, more productive pitchers produce lower ERAs, less productive pitchers produce higher ERAs. There are better stats, but to completely disregard it is throwing the baby out with the bathwater. It's a far cry from saying Kirby Yates is a bad pitcher because his record is 0-5. I understand that the eye test in baseball isn't a great way of interpreting results either because our minds often don't remember things exactly the way they happen and our eyes don't see everything that may be caught on Statcast or other analytical tools. But to assume that modern analytics can interpret all results scientifically is not something I believe with all variables involved. Often unintended consequences are even created by MLB managers as a result of decisions made using analytics. There are still many outcomes in baseball that are still either underquantified or overquantified by modern sabermetrics. Just my 2 cents.