2016 MORPS projections are finally ready. Unlike the baseline projections published several weeks ago, these projections include all players projected to win a MLB roster spot on opening day. I have also included a number of impact rookies who are projected to join a roster early or mid-season in 2016. Rookie projections use stats generated during either minor league or international play. Factors are applied to adjust the stats to MLB equivalent stats. MORPS projections also account for expected adjustments in personal playing time.
The excel version of the projections include a key tab that defines all headings used in the projections. In short, fantasy baseball players that play in rotisserie leagues should key on the R-ROTO and ROTO columns. ROTO is a point value derived from weights on the categories in a standard 5×5 rotisserie league. R-ROTO is the player ranking based upon the ROTO point values. If you league uses a customer scoring system, you can use the projections in the categories of interest to customize your rankings. Fantasy baseball players that play in a more realistic format like Baseball Manager or a similar simulation league should reorder the pitching based upon OERV and the batting based upon RC. OERV stands for Out Earned Run Value. This stat attempts to value a pitcher by combining ERA with the value of number of innings pitched. This is a way for fantasy managers in simulation leagues to compare the value of a relief pitcher with a starter or a starter who pitches 200 innings with one that pitches 100 with a slightly lower ERA. RC is Runs Created. A league like Baseball Manager uses RC as a basis for the points they generate in their daily games. The more realistic the simulation, the closer the hitting will align with RC.
For those who like to resort the projections for their own fantasy system, make sure you filter out the players with a roster status of “N”. These players will most likely not make an opening day 25 man roster. Those players who were still in competition for a position were included with a roster status of “Y” in most cases. I posted the “N” players for those managers who have keeper leagues or deeper rosters that may want to pull one of these folks onto their list.
Team projections for 2016 will be posted within the next week.
Most opening day rosters are set which means its time for the final 2014 MORPS projections. If you’re a Braves fan, you have to be wondering why your city is cursed. First its the traffic jam to end all traffic jams. Next, it’s all your pitchers getting hit by the injury bug. I’m hoping that some minor adjustments this year will yield even better results for this year’s projections. We’ll check in October to see how the numbers mapped to real stats.
For those who play Fantasy, remember to sort your stats for your scoring system. Baseball Manager (BBM) managers should sort batters by Runs Created (RC) and pitchers by OERV. This should yield the best results for simulation leagues that use real stats for nightly scoring. Roto leagues should use the projections as presented below.
MORPS updates for pitchers and batters are as follows:
Feel free to leave comments or suggestions.
MORPS projections are late coming this year. I’ve delivered a set of baseline projections several weeks ago. However, you’ll find that the actual projections have some drastic differences. I’m always amazed by the amount of player movement during the off season.
The Major-League Obie Role-Based Projection System (MORPS) uses four years of player performance data for all hitters. Since I started playing with Sabermetrics using Tango’s Marcel system, the first iteration of MORPS four years ago used the same formulas. After learning the basics, the batter formulas were adjusted to include the most recent four years of performance data. Adjustments were also made for player age, home ballpark data and expected playing time. The most complicated part of the system is the regression formulas. Tango provided formulas for his three year model. I had to crack open the math books to figure out how to transition the formulas to a four year model.
One of the most time consuming tasks in developing the system was determining the proper mean for player regression. If the goal was to ensure that the mean of all the projections competed favorably with end of year player means, the task would have been straight forward. However, my goal was to make the actual player projections as accurate as possible. “Role-Based” means that the player projections are regressed to position specific means. National League means are also separated from American League means.
While conducting research, I noticed that most projection systems used minor league stats as well as any available major league stats to project the future performance of young players. There are even formulas that anticipate player regression when entering the majors. The interesting thing is that Tango’s Marcel system does just as good at predicting rookie performance as other projection systems and he doesn’t use any minor league stats. Some players are great in the minors and simply can’t make the jump to the major leagues. Some players start out great, but find that major league pitchers start exploiting weaknesses they never knew they had. Others outperform all expectations. By calculating the reliability of a player’s projection using only major league data, MORPS adds a proportional dosage of a player’s positional mean to complete a rookie’s player projection. Since we are focused on individual player performance, I didn’t see the point of including all minor league stats when the results don’t seem to provide significant value. The last year of a rookies minor league or international season is included, with appropriate adjustments for competition, if no major league experience exists. While efforts have been made to adjust projections to reflect anticipated playing time, players who have a roster flag of “N” are projected using baseline projections only.
The formulas used to create pitcher projections are very similar to those that we have already discussed with batters. MORPS uses four years of data to create a pitcher projection. Adjustments are made for age, home field and anticipated role. The reliability of a projection is calculated based upon the amount of data available for a particular player. Someone with low reliability will regress more to a position specific mean than someone that has faced a lot of major league batters over the last four years.
The big difference between projecting pitchers and batters is the usage disparity between relief pitchers and starting pitchers. A good relief pitcher may face 350 batters in a season. A top end starting pitcher may pitch to 900 batters in a season. The plate appearances for position players are typically not dependent on role. A first baseman and shortstop may both have 600 plate appearances over the course of a year. Their position means will be different. First basement will typically have higher power stats while shortstops have higher speed stats. But, they are similar enough that their projections can be calculated using the same basic formulas. The disparity between relief and starting pitchers forces them to be calculated very differently. For months I struggled with pitching projections. When I finally figured out that starting pitchers and relief pitchers had to be calculated separately, everything fell in place.
I’ve received several emails asking about 2014 MORPS projections. My day job now includes travel which has left me less time to work on these projections. In the interest of time, I have put together a quick and dirty baseline version of 2014 MORPS projections. “What does this mean?” you may ask. Well… the short story is that the projections do not include any player team changes or role changes. I also did not error check. Will Cano’s stats go down in Seattle? Absolutely, but this set of projections have not accounted for his change in venue. You will need to take this into account if you are preparing for an early draft. Those things being said, the projection engine is the same one I automated last year. This means that the projections are still based on four years of data, positional mean regression, etc. In most cases, the numbers are fairly close to final values. Time permitting, I hope to publish a set of updated projections during Spring Training that include player roles and team changes.
Baseline 2014 MORPS Batting and Pitching projections are available in excel and PDF formats. Follow the links below to download your copy.
If you player Roto baseball, you will find the projections already sorted in Roto Rank order. If you play a more realistic version of fantasy baseball, like BBM, you will need to resort the XLS spreadsheet in RC order for batters and OERV order for pitchers.
Updates have been posted for both batting and pitching projections. These updates include all players that are currently projected to make each team’s 25 man roster according to MLBDEPTHCHARTS. A large number of non-roster players have also been included. However, non-roster players have not been “modeled” for MORPS projections. This means that their projection is based only on historical and mean data. All active players are assigned a rotorank prior to non-roster players. Thus, all non-roster players are at the end of the MORPS projections. This includes free agents. If some of these players actually win a roster position, compare their roto column to those of active players to decide where they should be slotted. For simulation leagues, you would use the RC column for batters and OERV for pitchers.
As players are signed and spring training position battles are settled, I will plan on updating the projections. This will occur periodically until the season starts.
It is generally accepted that the first fantasy baseball format that used live performance results was Rotisserie. It was started in 1980 by Daniel Okrent. The name comes from the place where the league met – a New York City restaurant called “La Rotisserie Francaise”. Rotisserie baseball is typically referred to by the number of batting and pitching categories that are monitored. A 4×4 roto league tracks 4 batting categories and 4 pitching categories. This format became popular because one could easily add up their player’s stats using weekly data information that was published in the USA today. In a 12 team roto league, the top manager would get 12 points in a category they lead, 11 points for second, etc. By adding all the category points together for those players you started that week, you derive the leaders (and eventual winners) of your league. Simplicity is the biggest strength of this format. You can run it just like a fantasy football league. Waivers are processed on one day. Weekly standings are published at the end of the weak. Etc. Etc. That is probably why this has become the largest fantasy baseball format. The negatives are the game does not reflect real individual player performance. Team stats like RBIs, Wins, Losses, etc. are dramatically impacted by the strength of a player’s team in lieu of their individual performance. Roto also doesn’t emphasize the daily nature of baseball. Everything is done on a weekly basis. In other words, the simplification that makes it popular to casual fans has also made it unrealistic for baseball purists. As real-time stats have become more accessible, many rotisserie variations have popped up. Head-to-Head leagues use rotisserie categories to award team wins, losses or ties on a weekly basis. Some leagues have even replaced traditional roto categories with sabermetric calculations.
Before rotisserie, a game called Strat-o-Matic (created in 1963) was the baseball diehard’s game of choice. Many didn’t consider this real fantasy baseball because live stats were not used. It was actually a tabletop game that used historical player data recorded on player baseball cards to simulate games and even seasons. Some sites still exist today that are built upon either historical or fictional player performance. All of these games have their roots in Strat-o-Matic. The pro of this format is that mangers often play a full 162 game season that has the daily feel of major league baseball. The obvious negative is that the game does not use live performance data. Thus, you are not really playing “fantasy” baseball.
In the early 1990s, a new game called Baseball Manager teamed with prodigy to create the first online fantasy baseball game. In order to recreate the real baseball feel of Strat-o-Matic and combine it with the live performance data associated with rotisserie, Baseball Manager chose to use newly created sabermetric projection systems to simulate daily head-to-head baseball games. The game engine combined live performances of players that played that day with banked performances that had not already been used in a head to head game. A fantasy manager’s team offensive performance was calculated by running their players thru the Bill James Runs Created formula. Defensive performances were a combination of pitcher ERAs and player’s fielding performance. A daily head-to-head game would be decided by comparing the offensive and defensive performance of each team. A daily sports page was published each evening for participating managers that read just like your local newspaper. Managers chose their daily lineups based upon pitching matchups (LH/RH); established their pitching rotations three days in advance like a major league manager and even simulated travel to an opposing team’s park to play a 3 game series. Although the game has obviously matured from the days of prodigy (web based), the basic idea of the game is still the same. The major positive of a simulation format is baseball realism on multiple levels. That is also the negative. Managers looking for simplicity or a draft and go type of league should not play simulation leagues. It isn’t a huge time commitment. But, you do have to spend some time on your team every few days. Over the last several years other simulation games have popped up that compete with Baseball Manager. Based upon second hand information, these other formats have resolution formulas that are not based upon sabermetric theory. However, I have not played these leagues so I don’t feel qualified to evaluate them within this post.
The last format that began emerging over the last 10 years is the head-to-head point leagues. These are very similar to roto in the sense that you draft your team and play baseball on a weekly basis. The difference is that the games use a resolution formula to award points for individual player statistical categories in lieu of ranking them from 1 to X. In a sense, they have attempted to use resolution formulas like the simulation leagues while maintaining the weekly format of roto. The positives and negatives of this format are really the same as roto. Simplicity, weekly formats, team based stats, etc. It is just a different way to represent the results.
You’ll notice that I did not discuss the various draft formats. I’ll attempt to cover that subject in another post since it seems that I have been typing on this topic for a while. Once you pick a format, this may be a differentiator for some managers.
So…, without further delay, the questions that you need to ask yourself when you want to choose a fantasy game are as follows:
1. How important is being part of the “main stream” of fantasy baseball?
a. Important – You should play rotisserie
b. Doesn’t Matter – Go to the next question.
2. What is more important to you – Simplicity or Realism?
a. Simplicity favors weekly formats like rotisserie and point leagues.
b. Realism favors simulation leagues.
c. Doesn’t Matter – Go to the next question.
3. Do you get bored with fantasy baseball within a month of finishing your draft?
a. Yes – You may want to try a more realistic version of fantasy baseball.
b. No – Go to the next question.
4. How long do you want to play – Full Season or Partial Season?
a. Full Season fantasy baseball is the standard for all fantasy baseball formats. Go to the next question.
b. There is only one format that offers a partial season – Simulation Leagues. Baseball Manager offers a lightning version that is 54 games in lieu of the standard 162.
5. How important is the level of competition that you play?
a. If you want to play the very best competition, you have three choices.
(1). Rotisserie winner leagues – Some sites allow managers who win within a public league to play in a winner league the next year.
(2). Money leagues – Managers typically only put big money into a league when they are serious about winning. Almost every format has money leagues.
(3). Progression Leagues – This is unique to the Baseball Manager Simulation leagues. In essence this is a fantasy pyramid scheme. There is one Tier 1 league, two Tier 2 leagues, four Tier 3 leagues, etc. If a manager wins a lower level league they are promoted to a higher tier the next year. The two bottom managers at the end of each year in each league are demoted to a lower tier. This is the only format I have played that has consequences for winners and losers. As a result, I have never seen an abandoned team in a progression league.
b. If you just want to win, public rotisserie and point leagues may be your best choice. Many of these sites suffer from abandoned teams and only a handful of quality managers per league. But, winning is certainly much easier in these formats.
c. If you really don’t care or you just want to have fun, you may want to go back and consider one of the other questions when choosing your type of league. You can always find a group of friends to play any format if fun is your goal.
I’m hoping these questions help you choose the fantasy baseball format that best fits your interests. Feel free to offer comments if there are other things that you found important when making your choice of formats.