Month: March 2017

A rankings list is the most common way to make decisions during a fantasy baseball draft. Here is a stab at a rankings list based on the projection distributions I released previously. It is calculated for a 12 team yahoo standard league.

 

	R	RBI	HR	SB	AVG	W	SO	SV	ERA	WHIP	total
Mookie Betts	11.8	11.2	10.0	21.9	9.8						53.8
Jose Altuve	11.3	10.0	8.6	25.9	10.4						53.2
Mike Trout	11.8	10.4	12.2	23.0	4.7						50.7
Max Scherzer						18.0	20.0	2.5	7.1	10.2	47.8
Paul Goldschmidt	10.9	9.6	10.8	23.0	3.7						46.5
Charlie Blackmon	10.5	9.6	9.1	18.6	7.9						46.4
Jean Segura	10.2	8.1	6.7	26.4	7.9						46.2

If you use this list, please note it hasn’t been updated for injuries, or playing time. Especially with closers, consult some other sources to make sure a closer has his job before drafting him. I noticed several players are commonly drafted following this system. Jean Segura, Brian Dozier, Jonathan Villar, Rick Porcello, Eduardo Nunez, AJ Happ, and Rajai Davis are players I’m getting in almost every mock draft I do. Other systems expect these players to regress to the mean more than my projection system, so you might discount them a lot or a little when drafting.

 

For Segura, he will now play half his games in Seattle, instead of Arizona. The other players just had breakout years. The possibility (even, the likelihood), of regression has definitely been factored in to the projection distributions. If you click on any of these names, you’ll see there are many possible outcomes where Segura regresses.

 

The total score isn’t an auction value. And, this system does not account for position scarcities. It’s designed as a rough tool to help you navigate a round robin, 12 team fantasy baseball draft. I hope it works for you.

 

Click For Full Rankings Table

Click to see the full table

Updated Projections for 2017 baseball. All the counting stats are the same, the update improves the projections for the ratio stats, batting average, earned run average, and WHIP.

Updated 2017 Major League Baseball Projections

 

In a previous post, I claimed numeric projections should be distributions. This is an example of something that can be built on top of such a projection system. It is an evaluation of a 12 team draft for a 5×5 fantasy baseball league.

Team 3 has a 30% chance of winning the league with this roster:

Evan Gattis Hou – C
Paul Goldschmidt Ari – 1B
Dustin Pedroia Bos – 2B
Kyle Seager Sea – 3B
Carlos Correa Hou – SS
George Springer Hou – OF
Giancarlo Stanton Mia – OF
José Bautista Tor – OF
Todd Frazier CWS – 1B,3B
Jake Lamb Ari – 3B
Carlos Martínez StL – SP
Cole Hamels Tex – SP
Jeurys Familia NYM – RP
Héctor Neris Phi – RP
J.A. Happ Tor – SP
Brandon Kintzler Min – RP
Chris Tillman Bal – SP
Jon Gray Col – SP

Distributions give more traction for calculating probabilities, all the way up the chain from player projections, to team-by-team category projections, and finally, probabilities for winning the league. I am working on a short essay on decisions to expand on these ideas, as well as an automated system for evaluating drafts.

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*quick note on the points histograms, the labels on the x-axis should be divided by 2

 

Here is a link to some raw projections for the 2017 baseball season:

2017 Major League Baseball Projections

I will add some updates in the next couple days to better handle the distribution tail information, which isn’t quite represented accurately in these histograms, and also to incorporate additional information like injury news and playing time news.