The 2015 Royals Dominated the American League

By Adam Gilfix

Tonight, the Kansas City Royals and New York Mets will play their first game of the 2016 season at Kauffman Stadium.  Just over five months ago, these two teams squared off at Citi Field when the Royals captured a World Series title in Game Five, one year removed from a heartbreaking loss at home in Game 7 of the Fall Classic.  As the new baseball season begins and 2015 fades further into the rear-view, it’s important to take a quick look back before we charge on ahead.

The 2015 Royals not only won the World Series for the first time since 1985, but also had the best record in the American League – something they had not done since 1977.  There was quite a bit of chatter about the National League’s regular season dominance: for the first time in history, the top 3 teams (Cardinals, Pirates, and Cubs) in Major League Baseball belonged to one division, the NL Central.  However, there wasn’t as much discussion about the Royals’ dominance of the AL.  This dominance was overshadowed by the extreme level of parity in the American League.  Five American League teams made the playoffs, but the next best five teams were within 6 wins of a postseason berth, with the other five not too far behind.  In fact, the 2015 AL exhibited arguably the most balanced competition in baseball history, owning the lowest standard deviation of team wins (a good measure of spread between teams) for a league with 15 or more teams ever.


That said, the Royals rose above this equal playing field and consistently controlled the AL last year.  Having read a fascinating article written by James Kushner for Baseball Prospectus in 1998 on quantifying the best teams in MLB history based on performance relative to each team’s league (American, National, and even ancient leagues like the American Association [AA]), I decided to update his rankings based on his methodology.  The basic principle was to calculate the Log5 – a “talent weight” – for every team every year and then take the Log5 of each team that finished 1st in its respective league and standardize it (by dividing by the standard deviation of the Log5 values of the rest of the teams in the league).  The resulting standardized value is what Kushner called “Competitive Quality Comparison Quotient,” or CQCQ, and is a good measure of teams’ dominance in their respective leagues (Kushner did not compare each team to MLB as a whole because of highly separated schedules for AL and NL).  Therefore, we can see below that the 2015 Royals, through a combination of winning baseball and historic league parity, just sneak in to the Top 20 “All-Time Best Teams according to CQCQ”.


Not that I want to overly celebrate 20th best all-time, but, considering that the sample size for teams that won their leagues in Major League Baseball history is 267, it is nevertheless an impressive feat for Kansas City.  In fact, prior to the 2015 Royals, no American League team laid claim to a spot in the Top 20 since the 1998 Yankees took 7th place on the list.

The 2016 MLB season should be another exciting one, though I doubt we will see quite as much parity in the AL as we did last year; after all, it is hard to repeat history like that.  Moreover, given the Royals dominance last season and solid roster turnover, don’t be surprised if this upstart, slap-hitting team finds itself playing some more October baseball.  Regardless, tonight’s season-opening rematch against the Mets will surely offer excitement, especially as the Royals raise the banner for the first time in 3 decades.

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  • Doesn’t divisional play skew these data in the same way that conference play skews data between the NL and AL? For instance, the Colorado Rockies play their divisional opponents 19 times, but other NL teams 6-7 times. So if a really really talented team happens to be in the same division as another really really talented team, that would make them look like a worse team than they actually are. So wouldn’t you have to standardize a team’s record against each other team to get a mini-winning % against each one and average them out?

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