Archive for Projections

Clayton Kershaw at Reduced Velocity?

Yesterday, I ran out of time while writing my MASH Report to look at how the possible effects of diminished velocity could have on Clayton Kershaw. Well, using a couple of untested, but promising ideas, it seems he will be may not struggle with less fastball speed.

The worries with Kershaw stem from this tweet.

He could be getting some of his strength back, but a possible 2+ mph drop could mean trouble for him. Kershaw’s fastball has at least averaged 92.5 mph in each of his six previous season. By looking at how he has produced previously at times with a lower velocities my indicate how he will do in the future.

Read the rest of this entry »


Examining Changes in Steamer Projections

In the preseason I used Zach Sanders’ method for deriving fantasy value from roto category statistics to see how the Steamer projections valued players from a fantasy perspective. The system essentially compares each payer’s production in each category and assigns standardized values for each player in each category. When you add those numbers up, you get a player’s fantasy value above average. After a quick adjustment for positional scarcity, you’ve got fantasy value above replacement (FVARz). In the preseason this was helpful to get an idea about who might be over or undervalued. Now I’ve taken the Steamer rest of season projections both to see whose value has changed the most in the month or so since the season started and to potentially help with making trades.

Today I want to highlight a few players that were not included in the original Steamer projections. Next week I’ll take a look at the players whose value has increased the most since the start of the season. Read the rest of this entry »


Hitter Results vs Unique Pitcher Types

We always hear our not-so-favorite broadcasters mentioning a player’s stats against a certain pitcher. Well, I think we are all hopefully smart enough to not take the results of 15 meetings between a pitcher and hitter seriously. Instead, we split samples into larger groups like right-handed hitter vs. left-handed pitcher. I have decided to cut the difference and create a spreadsheet which takes a middle ground. I grouped pitchers by handedness, velocity and groundball tendencies and found how hitters performed against the different pitcher groups.

First off, I wanted to have this Excel-only spreadsheet available online before the season started. Well, I got it done and working in time. Since Visual Basic macros were used in the final view, it doesn’t have a online option which I wanted. So today, I am going to make it publicly available, but at some point I hope to have it working in all spreadsheet formats and/or online at a place like Google.docs.

Read the rest of this entry »


More On Spring Stats And Power, With An Eye on Chris Heisey

On Tuesday, I wrote about wrinkles that I tried to add to the so-called Dewan Rule, hoping to leverage spring training statistics to help predict breakouts. It didn’t work, as was somewhat expected. In fact, Dewan himself admitted on Wednesday that the rule no longer seems to work.

However, a suggestion in the comments section led me to study the same data from a different angle, and it now seems a bit more promising.
Read the rest of this entry »


Eight and a Half Observations Using ZiPS Projections

So, you may have heard that ZiPS projections are now available for 2014. You may also be wondering if said projections reveal information pertinent to your fantasy drafts. Well, let me tell you.

Read the rest of this entry »


Stolen Topic: Three Players I Won’t Draft

Bender wrote about three players he would not draft yesterday, and I thought I’d pitch in with three of my own. These kinds of posts convey a lot of information about where the writer thinks the marketplace really diverges from reality, so they can be among the most useful when preparing for a draft. I’m not saying that you should take what we say as gospel, but if your own expectations are substantially different than ours, it might be worth taking a second look.

Read the rest of this entry »


Fantasy Rankings Prep (3 of 3)

I am going to finish my fantasy ranking series today (Part 1 and Part 2). Today, I am going to look at how I set up my draft ranking.  It is a little unique, but indispensable for finding draft day values, but I first need to clear up one issue from yesterday.

I am going to go over one problem people are noticing which is how high catchers are in my rankings and the lack of Robinson Cano. Well here are my projections for each. If you disagree, that is a different discussion, I am just looking at the difference in replacement level values:

Read the rest of this entry »


Fantasy Rankings Prep (2 of 3)

In my last article, I went over the initial work for valuing players in a basic fantasy league (12 5×5 teams with 23 roster positions).  Each league has its own unique rules so the procedure may need to be adjusted accordingly. Today, I am going to finish the positional rankings and begin to come up with an overall ranking.

Read the rest of this entry »


A Collection of Five Category Hitters

When drafting hitters for a traditional five category league, my standard strategy is to target players who contribute in many categories – preferably all five. Today, in deference to my jet lag, we’re mostly going to dispense with analysis and break out some lists of players who fall into different buckets of production. All of the values below come from Steamer’s 2014 projections. Steamer and projection systems in general aren’t the best at predicting runs and RBI, so keep that in mind.

Read the rest of this entry »


MASH Report (11/19/13) – Starting Pitcher DL Projections Reviewed

Today I will check back on my 2013 Starting Pitcher DL Projections. Additionally I have injury updates on several players.

• Before last season, I projected the chances a starting pitcher would go on the DL given a formula I created a few season. I took into consideration age, previous MLB experience and past injuries. It is time to see how it did.

First, I removed pitchers who were not on a team in 2013 like Kevin Millwood and Randy Wolf. Next, I added the DL percentage chances for the remaining pitchers. The formula predicted 44.8 pitchers were DL bound. In reality, 44 went on the DL. I will take it. Additionally, I looked at the 20 most and least likely players to go on the DL. Of the twenty least likely, I predicted 6.2 to go on the DL and the actual number was five. Looking at the most likely candidates, I predicted 9.9 to go on the DL and nine actually went. Overall, the results were outstandinga and I will put out the 2014 prediction at a later date.

Read the rest of this entry »