Mandatory Credit: Kevin Jairaj-USA TODAY Sports
As we inch closer and closer to the beginning of the 2014 season, we start to see more and more predictions for players and teams from fans and media outlets alike. The Royals are already getting some love from national pundits like Buster Olney and Bob Nightengale, and I’d expect to see a few more analysts join them in the next couple of months, if only because Kansas City could be the “sexy” pick. A lot of times, people can be swayed by emotion and storylines, which is fine. Sports always have emotional connections. However, being the stat nerd that I am, I often enjoy removing as much bias as possible, and just using whatever objective data available to make predictions. The best way to do that, in my opinion, is with projection systems.
I should preface this by saying that no projection system is perfect, and even mathematic algorithms can have their biases. But these systems are based on tons and tons of historical data, and usually are reliable enough to give a rough idea of what to expect in the following season. Dan Szymborski does excellent work with his ZiPS projections, but since he has yet to release those for the 2014 Royals, I wanted to look at the Steamer projections. The full link can be found here.
There are a lot of numbers there, so instead of taking each player one by one, I thought it might be best to just offer some quick observations on the things that stood out the most.
– First of all, even after Billy Butler’s somewhat underwhelming 2013, he’s still projected to be the best hitter on the team, with a wOBA of .363.
– Alex Gordon is also projected to bounce back from a disappointing offensive season, in both his plate discipline (projected 9.5% BB rate), and power (projected .168 ISO).
– The Steamer system appears to be more optimistic on Mike Moustakas than one would expect. A .740 OPS is far from an MVP-level of performance, but it’s a bit above average, and combined with his defense, Moose is projected to be a very solid player.
– Johnny Giavotella’s projection puts him just below the offensive level of Moustakas. Granted, that would come in a small sample size, but small samples have been used to judge Gio’s entire career, so why stop now?
– Both of Dayton Moore’s biggest offensive acquisitions are projected to be just above average, with 2.1 WAR each.
That last point leads me to what I find most interesting about these projections:
The Royals project to have 8 of their 9 starting position players perform at an above average level.
If we accept that a typical major league average player is worth 2 WAR, the only regular player in the linked table to fall below that line is Escobar. Similar to what I said about the lineup in comparison to previous Opening Day lineups, this roster appears to be quite talented. The 2013 team had 6 players above 2 WAR. The 2012 team had 5. In 2011, there were just 3. In 2010, there were 2, which is the same number of 2+ WAR players the 2009 team had. The 2008 squad had 3 such players. Even the 2003 team only had 3 above average players. I could go on, but to save myself from writing (and you from reading) several hundreds of extra words, I’ll stop there.
The Royals have never had 8 players produce 2+ WAR in a single season in the franchise’s history.
They’ve only had 1 season in which more than 6 players were worth 2+ wins, and that was in 1982, when 7 players did it. Now, this doesn’t mean the 2014 Royals are going to be the best squad in team history. There are no MVP-caliber projections in the table, but there is a lot of balance. Obviously it would be great to have a Mike Trout or Miguel Cabrera in there, but there is still value in having above average players all over the field, or at least almost all over the field.
As I said above, projections aren’t perfect, and the numbers above may look much different at the end of the season. But based on the data available, they’re definitely good starting points for predictions, and without a lot of actual news happening, they make for great discussion points during a cold, cold winter.