FREE MLB Player Forecasts, Rankings

About the Guru's MLB Player Projections, Rankings - The spreadsheets below have 6 tabs: Definitions (descriptions of stats), Demo (batter details), Batting forecasts, Pitching forecasts, and Cheat Sheets for batters and pitchers. The names of the forecasted stats have an "m" in from of them. So, the HR forecast is mHR, etc. Players with no MLB experience do not have forecasts. 

Forecasts are based on data from the last three years, where recent years count more. Some of last years stats are included as a reference. Some stats are our own invention (described below). And, for pitchers, 2 and 3 year forecasts for key stats are included, but take these with a grain of salt.

For ranking players, the mGURU stat is the key. Alternatively for batters, use mGURUwt, which weighs by positional scarcity. mGURU is designed to weight the players rate of production and expected playing time to arrive at a best rating. Since forecasting playing time is difficult (although we are proud of the strength of this forecast), mGURU is weighted more heavily on rate than tradition linear weights. This strategy is useful for the goal of ranking player forecasts for simulation leagues.

mGURU is calibrated to value batters and pitchers roughly equally, possibly giving a slight edge to pitchers. It does not consider fielding. For batters, SB's are not as valuable in real life (or in mGURU) as they are in rotisserie, so draft accordingly.

mROTO is designed to provide values for 5x5 rotisserie scoring as follows: Batting is Avg, HR, SB, RBI, R. Pitching is ERA, W, SV, WHIP, Strike outs. mROTOwt weights values by positional scarcity. Values are meant to be relative to each other and provide directional guidance. Values resemble mixed leagues with a $260 budget for 12 teams.

NL players are listed at the top, AL at the bottom. If you are playing in a mixed league, for batters: sort by Play (descending), POS (descending), mGuru (descending); for pitchers sort by Play (descending), POS (descending), mGURU (descending). In the case of pitchers, notice that positions were newly defined to distinguish between them (see below).

Players can also be sorted by rankings. Rank is overall for batters.lrank is the league rank among either batters or pitchers. prank is the positional rank within league for either batters or pitchers. An overall rank across all players was not made, but it can be infered using mGURU.

If you prefer not to consider playing time in the rankings and want to reply soly on rate of production, we have that too. For batters use wOBA, which is based on research by Tom Tango. For Pitchers use mDERA, which is the ERA forecast. It relies heavily on Voros McCracken's DIPS concept. ERAi is the indexed to league ERA.

No minor league data was considered, so be advised that forecasts for rookies tend to be weighted more heavily towards league averages for players of their positions and expected playing time than established players. Another stat Tom Tango developed called Reliability will help you gauge this. Best of all is to look at the 3 similar players players the machine identifies.

ORIGINAL INSIGHTS

Before we get into the numbers, consider the machine learning text. It tells us which players are the most similar using an original approach and clusters them and gives us a brief description of their status.

ORIGINAL BATTING STATS

The xGURU and xwOBA for batters shows expected batting value for someone at that position and playing time. So if you want to consider valuing SS over OF, then see how much higher that persons mGURU is above xGURU. mGURUwt was created to do this weighting for you.

mStarter is predicted playing time, where Y is Starter; N is Not full time Starter or Inj risk or Performance Risk; and B is a Bench player with fringe mlb-level quality forecasted.

mVORP is Value (runs contributed) Over Replacement Player. It is similar to WAR, but uses a different bar for replacement value. For batters this is the wOBA of non-starters at each position. The formula is (mwOBA-xwOBA)*mTAP. This is different from mGURU, which further weights the results against players of similar playing time. mGURU is also weighted more towards rate of performance, so times at plate plays less of a factor (although it still matters).

ORIGINAL PITCHING STATS

Creation of pitching positions: SP=Starters / LP=Long Relief (Swing) / JP=Junk (or Junior) Starters / EP=Elite Relief Pitchers / DP=Decent RP / BP=Bad RP/ AP=Avoid RP. These assignments are critical for drafting. Seriously, do not draft AP or JP pitchers, no matter what the machine thinks. And, LP might also stand for "Last to Predict" because I don't know what to do with these guys (neither do most others, but at least Iadmit it). I don't have supporting minor league data and LPs are players in flux. Look for bargains and young talent there.

mSTUFF (Do NOT confuse this with PECOTA's stuff). Having big STUFF means excellent power and control. Its our way of measuring upside, especially for young pitchers. Find hidden future stars! The formula is: 6*mDOM -2.67*mDERA -3*mCTL -5*mHR9; if mSTUFF<1 then mSTUFF=1; mSTUFF=mSTUFF*mSTUFF/10;

WRIP - Since hrs allowed are more under a pitchers control than hits allowed, a stat called wrip was created to look like whip. Whip is (walks+hits)/ip and Wrip is (walks+hr*10)/ip. I also like the names because a pitcher giving up lots of hits gets "whipped", while one giving up lots of HRs gets "wripped." Agree?

mVORP is Value (runs allowed) Over Replacement Player at same position. It is similar to WAR, but uses a different bar for replacement value. It is (mDERA-xDERA)*mIP. xDERA ranges from 6 for someone who only starts to 5 for somone never starts. Like WAR, which is based on FIP instead of ERA, this is based on mDERA, which is much more like FIP than ERA.

traj indicates the trajectory the pitcher is heading over the next 3 years.

Several more are borrowed from others, such as: mCMD (9*bb/ip), mDOM (9*k/ip), mCTL (k/bb), and HR9 (9*hr/ip). 

 Forecasts from Past Years
Actuals and forecasts include original guru stats and other sabermetrics.

Work was done every year to improve the forecasts and add insights!