The Only* Division Race in Baseball

With the start of the regular season just four days away, we find ourselves in the thick of preview season. No matter where you look, it all boils down to the question: what’s 2016 going to look like? At FanGraphs, we’ve just wrapped up our yearly Positional Power Rankings that assess the season through the lens of each position.

As you might have noticed, each team is made up of the sum of these positional projections and they will all start playing together as 30 units in nine-inning contests next week. If you’re into that sort of thing, we offer Playoff Odds that estimates each club’s shot at postseason baseball (explained here).

It’s important to remember, for all the reasons cited in the previous link, that these projected standings are incapable of total precision. In reality, even with a perfect model for individual player projections, you still wouldn’t hit on every team. And we don’t have anything close to a perfect model for individual players. Yet these projections do offer an objective reading of where the teams stand relative to one another based on what we know. They might wind up being wrong, but they’ll be wrong because they’re flawed not because they’re trying to write an interesting narrative.

Despite clear signs of parity, especially in the American League, our projections think only one division is going to be particularly close: the National League East.

Let’s pull it together visually for clarity. This graph shows the difference in the odds of winning the division for the top two teams in each division. The only two teams within 27% of each other are the Mets and Nationals at 52.8% and 42.1%, respectively. Keep in mind these projections change as we learn about playing time, so if you’re reading this a day or two after publication, it might be a bit different:

Of course, this is the estimate of one system. Baseball Prospectus’ PECOTA, for example, thinks the AL East will be very competitive. Setting aside the fact that the projections aren’t perfectly accurate and that our model likely has flaws, let’s focus on the only interesting division race, according to the FanGraphs Depth Charts.

If you look at the race in the aggregate, the Mets’ projected WAR of 47.3 lines up favorably with the Nationals’ mark of 42.6. Mets position players stand at 24.1 WAR compared to the Nationals’ 21.1. On the pitching side, Mets starters lead 19.7 to 18.1 and the relief split is 3.6 to 3.1 in favor of the Mets.

If baseball were solely the result of independent, context neutral events, we’d probably have the Mets favored by a lot more than 10% in the NL East. But when you turn to the simulations, which take into account the construction of the team and the schedule they will play, the Nats close the gap to roughly one win.

In each facet of the game, the Mets are slightly ahead of the Nationals, but if we break into the individual positions, the story looks a little different. The Mets project to be better than the Nationals in seven of nine spots. Anthony Rendon leads David Wright at third base, but the huge difference is Bryce Harper’s lead over Curtis Granderson in right. Granderson is a solid player, but Harper is probably one of the five best players in the game. Observe:

The starting pitching battle is a little less funky. Scherzer projects to be a step ahead of deGrom/Harvey, but Noah Syndergaard and Steven Matz make up the difference when they’re lined up against Gio Gonzalez and Tanner Roark/Joe Ross.

#1 Mets

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Name	IP	K/9	BB/9	HR/9	BABIP	LOB%	ERA	FIP	WAR
Jacob deGrom	202.0	9.3	2.3	0.8	.302	75.6 %	3.00	3.00	4.9
Matt Harvey	209.0	8.8	2.1	0.8	.297	74.8 %	3.00	3.05	4.9
Noah Syndergaard	182.0	10.0	2.3	0.9	.306	75.5 %	3.12	3.04	4.3
Steven Matz	159.0	8.8	2.9	0.8	.306	73.9 %	3.48	3.49	2.8
Bartolo Colon	113.0	6.1	1.3	1.1	.306	70.8 %	3.98	3.87	1.5
Zack Wheeler	65.0	8.7	3.5	0.8	.308	72.9 %	3.72	3.72	1.0
Rafael Montero	28.0	8.3	3.1	1.0	.304	72.8 %	3.87	3.87	0.4
Gabriel Ynoa	9.0	5.3	2.1	1.4	.305	67.1 %	5.03	4.86	0.0
Seth Lugo	9.0	7.7	3.1	1.3	.307	70.0 %	4.59	4.47	0.1
Total	976.0	8.8	2.3	0.9	.304	74.1 %	3.32	3.30	19.7

#4 Nationals

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Name	IP	K/9	BB/9	HR/9	BABIP	LOB%	ERA	FIP	WAR
Max Scherzer	211.0	10.6	2.1	0.8	.304	78.2 %	2.70	2.71	5.8
Stephen Strasburg	182.0	10.2	2.0	0.8	.310	76.2 %	2.92	2.83	4.7
Gio Gonzalez	170.0	8.6	3.4	0.7	.311	72.9 %	3.58	3.43	3.1
Tanner Roark	132.0	6.2	2.2	1.0	.301	71.7 %	3.91	4.01	1.4
Joe Ross	121.0	7.5	2.7	1.0	.304	71.7 %	3.88	3.86	1.5
Lucas Giolito	94.0	8.3	3.3	1.0	.306	72.1 %	3.97	3.94	1.1
A.J. Cole	19.0	7.0	2.5	1.2	.301	72.6 %	4.07	4.25	0.2
Yusmeiro Petit	19.0	8.0	1.9	1.2	.304	72.9 %	3.86	3.82	0.2
Taylor Jordan	9.0	6.0	2.4	0.9	.309	69.8 %	4.11	3.98	0.1
Total	957.0	8.8	2.5	0.9	.306	74.0 %	3.40	3.37	18.1

In the bullpen, the teams look similar at the back end, but the projections favor the Mets’ middle relief.

#9 Mets

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Name	IP	K/9	BB/9	HR/9	BABIP	LOB%	ERA	FIP	WAR
Jeurys Familia	65.0	9.8	2.7	0.7	.301	76.8 %	2.83	2.98	1.4
Addison Reed	65.0	9.0	2.9	0.9	.305	74.6 %	3.48	3.51	0.7
Antonio Bastardo	55.0	10.6	4.1	0.8	.297	76.6 %	3.28	3.45	0.5
Hansel Robles	55.0	10.0	3.1	1.0	.297	75.9 %	3.31	3.47	0.4
Sean Gilmartin	45.0	8.4	3.0	0.8	.304	74.1 %	3.42	3.51	0.3
Erik Goeddel	40.0	8.6	3.4	0.9	.303	72.1 %	3.78	3.72	0.1
Logan Verrett	35.0	7.6	2.1	1.1	.302	71.9 %	3.87	3.86	0.0
Bartolo Colon	30.0	6.1	1.3	1.1	.306	70.8 %	3.98	3.87	0.0
Jim Henderson	25.0	9.5	3.7	1.1	.304	73.0 %	4.05	3.98	0.0
Jerry Blevins	20.0	9.3	3.0	0.9	.298	75.7 %	3.28	3.49	0.0
Dario Alvarez	15.0	10.0	3.9	0.9	.306	75.0 %	3.55	3.73	0.0
Josh Smoker	10.0	9.4	4.0	0.9	.307	73.1 %	3.75	3.74	0.0
Akeel Morris	10.0	10.7	5.0	0.9	.306	74.4 %	3.76	3.84	0.0
Josh Edgin	10.0	8.7	3.6	0.9	.300	74.5 %	3.57	3.78	0.0
Jeff Walters	10.0	8.5	2.8	0.8	.303	72.8 %	3.54	3.51	0.0
Total	482.0	9.1	3.1	0.9	.302	74.5 %	3.45	3.52	3.6

#11 Nationals

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Name	IP	K/9	BB/9	HR/9	BABIP	LOB%	ERA	FIP	WAR
Jonathan Papelbon	65.0	7.8	2.1	0.9	.299	74.8 %	3.32	3.55	0.6
Shawn Kelley	65.0	10.5	3.1	0.8	.309	76.8 %	3.04	2.99	1.2
Blake Treinen	55.0	8.4	3.1	0.6	.311	74.3 %	3.23	3.25	0.7
Oliver Perez	55.0	10.4	3.4	0.8	.313	76.1 %	3.26	3.34	0.5
Yusmeiro Petit	45.0	8.0	1.9	1.2	.304	72.9 %	3.86	3.82	0.1
Matt Belisle	40.0	6.9	2.9	0.7	.312	71.9 %	3.80	3.71	0.1
Trevor Gott	35.0	7.3	3.6	0.7	.305	72.0 %	3.81	3.87	0.0
Felipe Rivero	30.0	8.3	3.0	0.7	.298	74.5 %	3.32	3.43	0.1
Rafael Martin	25.0	10.3	3.0	0.8	.309	76.3 %	3.16	3.18	0.1
Abel De Los Santos	20.0	8.1	3.0	1.0	.305	73.0 %	3.89	4.02	0.0
Burke Badenhop	15.0	5.6	2.5	0.7	.307	71.0 %	3.86	3.84	0.0
Sammy Solis	10.0	7.2	2.9	0.7	.306	72.0 %	3.74	3.70	0.0
Matt Grace	10.0	6.7	3.2	0.7	.309	71.7 %	3.83	3.84	0.0
Nick Lee	10.0	8.8	6.1	0.9	.305	72.5 %	4.44	4.62	0.0
The Others	21.0	8.2	4.0	1.2	.322	69.5 %	4.73	4.50	0.0
Total	501.0	8.5	3.0	0.8	.307	73.9 %	3.52	3.55	3.4

Clearly, the story is that the Nationals have a lot of their eggs in the Bryce Harper and Max Scherzer basket. It’s a wonderful basket filled with flowing hair and multi-colored eyes, but that doesn’t mean it isn’t susceptible to injuries just like the less talented baskets. Without Harper or Scherzer, the Nationals would be in serious trouble. The Mets would obviously prefer not to lose deGrom or Harvey, but it would be a much easier hit to take.

This is probably an under-appreciated aspect of roster construction. Generally, we don’t think of two 3 WAR players being much better or worse than one 6 WAR player from a performance standpoint, but when you’re forecasting health it gets a little more complicated. In order for the Mets to lose 6-7 WAR, they need to suffer two major injuries. The Nationals just need to suffer one to either of their stars.

Teams almost certainly take this into account when working up contract offers and offseason strategies, but it’s not something we talk about very much when discussing projections. The uncertainty surrounding the projections for teams that have a lot of value concentrated in just a few players is higher than the uncertainty for a team where the talent is distributed more evenly throughout their roster. Phrased another way: while the projections represent median forecasts for wins, the distribution of wins likely isn’t uniform around those midpoints.

If the odds of a season-ending injury for any given player is 5% (number illustrative only), then there is something like a 9% chance that at least one of two players goes down, but only a 1% chance that both go down at the same time. Obviously things get more complicated as you increase the number of players in your population, but there is definitely a difference between assessing the odds of a serious injury and assessing the odds of typical under-performance. There’s upside to stacking talent in a few spots, such as roster flexibility and an easier ability to upgrade at the deadline, but it’s a higher risk strategy for sure.

Our projections think the Mets and Nationals will be locked in the closest division race in the game this year. They think the Cubs will run away with the NL Central and that the Dodgers, Astros, Indians, and Red Sox are in comfortable positions ahead of Opening Day. Even the youngest reader has been around long enough to know things won’t work out the way the projections expect because the projections just don’t have enough information to accurately predict a baseball season.

But right now, the projections are telling us that, on paper, the Mets and Nationals are closer in talent level than any other set of division rivals. Players will get hurt, breakouts will happen, and some will have down years. These projections aren’t a road map to the end of the season, they’re a quick assessment of what we know at this moment. For now, they’re telling us that the tightest race is between the Mets and Nationals and that Bryce Harper is the only thing* that stands between us and six months of inconsequential baseball.