Sonny Gray – aka “The Oxymornic Forecast” – stormed through Texas with a 3-hit shutout (6 K’s) that netted him his 4th win and an ERA/WHIP of 1.76/1.14. Not bad for a 16-year old if you ask me. Is he getting a little lucky? Yes he is, question I just asked myself. But he certainly looks like (at least) a top 25 SP right now and has the benefit of a nice home park. Makes me wish I had him on one of my eleventy teams (why don’t you like him Steamer?)

Anyway, the other oxymoronic Grey asked me to pinch-hit as he was going to a ‘one-man show’ tonight. Hoping that isn’t code for renting a hotel room by himself and running up adult movie charges on the Razzball corporate card.

Please, blog, may I have some more?

I typically keep these expert league draft write-ups short but I think this year’s Yahoo! Friends & Family draft was an interesting draft to both:  1) Share some of my in-draft thinking and 2) Go off on tangents based on a couple of interesting draft gambits.   So apologies in advance for the Tolstoyan/Grantlandian length of this post.

Fantasy baseball draft rooms feel like poker tables.  Now I do not play a lot of poker but, for analogy’s sake, I’ll say there are two types of tables when you play with good players:  1) Strong but predictable play with occasional risks/bluffs and 2) Unpredictable but strong play that takes you out of your comfort zone.

Most leagues we play in fall under the former for 15-team mixed snake drafts (AL/NL-only auctions a whole different beast).  There really was not a moment in this year’s 15-team mixed LABR and KFFL drafts where I felt uncomfortable.  I had a general strategy, my values, and the NFBC ADPs. All peachy.  I am not saying I dominated those drafts – just that I felt pretty comfortable.  It did not hurt that I picked 8th in both those drafts so I did not have to worry as much about position runs.

Please, blog, may I have some more?

Loyal (or at least frequent) readers of this site know that Grey LOVES to rub it in my face whenever he is right about a player and I am wrong.  I think he has an archive of every conversation we ever had for that expressed purpose.  It’s like he is keeping an NSA dossier on me and the S stands for Spite.

In the spirit of transparency – and maybe actual learning – I stitched together our 12-team mixed $ values for 2014 so there is a complete comparison out there for you to see.  I am only including players where one of us gave the player a $0+ value as once you agree a guy is undraftable, there is no reason for further debate.

Please, blog, may I have some more?

We know how easy it is to just click on a player’s name from within your fantasy baseball league site when you want to find out more information/stats on the player.

But we feel confident that no site’s player pages can help you as much as Razzball’s redesigned player pages to make quick and informed day-to-day fantasy baseball decisions.

Here are examples of the redesigned hitter and pitcher pages.

Please, blog, may I have some more?

I was fortunate enough to be invited to this year in KFFL’s Fantasy Baseball Analysis Draft (which leads to a BAD acronym).  It has historically been a 12-team mixed snake draft league but has now been expanded to 15 teams.

Some drafts require a lot of prep time – this one had the prep time of a TV dinner.  It came right on the heels of LABR which follows the same format.  Then my pals at KFFL (Nick Minnix and Tim Heaney) were nice enough to ‘randomly’ assign me the same pick (#8) I had in LABR.  Sweet.

My strategy going into the draft was similar to LABR – draft 9+ SPs, be AVG-conscious, get two top 15 closers, try to nab one of the speedy/solid AVG MIs, and anticipate and/or dodge position runs.  There were a couple of post-LABR draft learnings I incorporated:

This is a post for the fantasy baseball drafters who use Excel, Google Docs, or some other war room software that automatically totals a drafted team’s stats while in the middle of a draft.  Or perhaps for those of you who do mock drafts or simulated drafts.

The below grid represents my projected 75% mark in each stat category across 10/12/14/15/16 team ESPN and Yahoo default roster format leagues.

These numbers should only be used directionally.  Please note that each projection source projects to a different league average so your team may look great if using a ‘bullish’ source and look poor if using a ‘bearish’ source.

Personally, I ignore team totals throughout a draft and go by feel in terms of my team’s balance.  While I have had regrettable drafts over the years, I do not recall one that failed because my team was not balanced enough.  If I do happen to have the time and curiosity to do an in-draft litmus test, I just add up the dollar values per category to see which categories are lowest.

Please, blog, may I have some more?

This is part of a four-part series using Rudy and Grey’s Razzball Commenter League experience as well as some modeling (the dorky kind) to quantify the effectiveness of streaming and how it should inform one’s draft strategy in shallow mixed leagues (10-12 teams).  The first three posts will focus on quantifying the value of streaming starting pitchers, relief pitchers, and hitters.  The fourth will synthesize the learnings from the three and how they impact draft strategy.  The streaming decisions made by Grey and I were HIGHLY influenced by our free, daily updated tools for streaming starting pitchers (Stream-o-nator) and hitters (Hitter-tron).

If you are reading this article (or this site for that matter), I assume you are familiar with streaming starting pitchers.  This is an essential strategy in all daily league formats whether one plays standard Roto or H2H.  While my beloved Stream-o-nator aims to make sure all our readers make the most informed decisions on which pitchers to stream over the next 7 days (and possibly more in 2014), I have yet to read any analysis that quantifies the value of the average streaming pitcher to inform draft strategy.  So this post is going to focus on quantifying the value of a streaming SP and, once I’ve completed quantifying the value of streaming relievers and hitters, I will figure out how this impacts draft strategy.

Please, blog, may I have some more?

This post is a sequel to this post on maximizing ABs.

In recent posts, I used the results of our 2013 Razzball Commenter Leagues (based on 64 12-team mixed leagues with daily roster changes and unlimited pickups) to show:

So this leaves 41% of Pitching Standings Points that could be attributed to a manager’s in-season moves.

Please, blog, may I have some more?

In recent posts, I used the results of our 2013 Razzball Commenter Leagues (based on 64 12-team mixed leagues with daily roster changes and unlimited pickups) to show:

So this leaves 30% of Hitting Standings Points that could be attributed to a manager’s in-season moves.

Inspired by one of our commenters (initials SF), I thought of a way to reduce the size of that 30% black box.  While estimating the quality of a manager’s in-season moves is very complicated, estimate the quantity of a manager’s moves is EZPZ.  That would be interesting…..but what kind of guidance would that provide?  Making roster moves just for the sake of it is a waste of time and if you, our loyal readers, are going to waste your time, we prefer you do it on our site vs. your league site.

Please, blog, may I have some more?