2013 Projections for the Baltimore Orioles

With opening day of the 2013 regular season just around the corner, I thought it would be fun to look at a couple of projections for the AL East and some Orioles players to see how fancy schmancy computer programs thought this year would turn out. And if you’re a fan of the Orioles, you probably won’t like what you see.

Zips Projection System

First up is the Zips projection system, which was created by Dan Szymborski (used at Fangraphs). On Tuesday, Szymborski posted an article on ESPN projecting the standings for each division (Insider subscription required). How does Zips work? According to Szymborski:

“Seasons are simulated a million times using a Monte Carlo method, the percentile performance of player projections and estimates of roster construction.”

The Fangraphs Library also has a definition if that wasn’t enough. In addition to projected wins and losses, the table includes (in order) the percentage each team has to win the division, finish in last place, earn a wildcard, make the playoffs, and win the world series.

Team	W	L	GB	PCT	DIV%	LAST%	WC%	PLAYOFF%	WS WIN%
Toronto	94	68	—	0.580	42.90%	5.80%	25.20%	68.10%	6.90%
Tampa Bay	88	74	6	0.543	23.10%	13.40%	25.80%	48.90%	4.50%
Boston	84	78	10	0.519	13.20%	23.30%	20.90%	34.10%	3.00%
New York	83	79	11	0.512	11.30%	26.70%	18.40%	29.70%	2.60%
Baltimore	82	80	12	0.506	9.50%	30.70%	16.70%	26.20%	2.20%

If you’re wondering how the projected lineup and starting rotation are expected to perform, you’re in luck…

Projected Opening Day Lineup

Name	POS	AVG	OBP	SLG	WAR
Brian Roberts	2B	0.244	0.309	0.363	0.2
Nick Markakis	RF	0.281	0.350	0.428	2.0
Adam Jones	CF	0.277	0.326	0.474	3.6
Matt Wieters	C	0.256	0.330	0.433	4.5
Chris Davis	1B	0.252	0.308	0.450	0.9
J.J. Hardy	SS	0.258	0.304	0.424	3.5
Nate McLouth	LF	0.231	0.318	0.379	1.2
Nolan Reimold	DH	0.246	0.322	0.420	1.0
Manny Machado	3B	0.252	0.311	0.418	2.7

Projected Starting Rotation

Name	W	L	ERA	WHIP	K/9	BB/9	FIP	WAR
Jason Hammel	9	6	3.72	1.27	7.98	2.98	3.59	2.5
Wei-Yin Chen	10	8	4.10	1.23	4.86	1.85	4.44	1.3
Miguel Gonzalez	6	7	4.57	1.43	6.60	3.61	4.59	0.3
Chris Tillman	14	12	4.29	1.31	6.90	3.04	4.44	1.3
Jake Arrieta	8	11	5.16	1.51	7.09	4.23	4.81	0.5

PECOTA

If you didn’t find the projection provided by the Zips system to your liking, you should probably stop reading, because the PECOTA projection system developed by Nate Silver and Baseball Prospectus looks worse. To make its projections, PECOTA relies heavily on statistics in a player’s previous seasons and statistics of historically similar players.

Team	W	L	GB	PCT	DIV%	WC%	PLAYOFF%	WS WIN%
New York	88	74	—	0.541	45.8%	21.2%	67.0%	9.0%
Tampa Bay	85	77	2	0.525	25.4%	23.5%	48.9%	4.7%
Boston	83	79	5	0.511	15.0%	19.0%	34.1%	2.6%
Toronto	82	80	6	0.506	12.0%	16.2%	28.2%	2.0%
Baltimore	75	87	13	0.462	1.7%	3.4%	5.0%	0.2%

As you can imagine, the individual player projections in PECOTA aren’t as high on the Orioles players as Zips, and I don’t want to add to the negativity of this column, so we’ll leave those out.

So what is the take away of this? Well there’s good news and bad news. The bad news is the projections don’t think the Orioles have much of a chance to return to the playoffs. The good news is that last year, the Orioles made the playoffs when the projection systems didn’t give them much of a chance. There is a reason why the games are actually played, and it’s because no matter how sophisticated a computer model you have, it can’t predict the future, and it sure can’t predict baseball.

On that note, happy Opening Night and enjoy the season!

This entry was posted on March 31, 2013 at 10:26 pm and is filed under Offseason, Projections with tags PECOTA, Zips. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.

Orioles Proving Ground