2016 MORPS Baseline Projections

The 2016 MORPS baseline projections are ready.  This is the third year we have provided baselines. These projections use all the models we have put together over the years for projecting player performance.   This means that the projections are still based on four years of data, positional mean regression, etc.  However, they do not account for a player changing positions, reductions in playing time, new players to the big leagues, etc.  We entered all MLB player transactions into system since the end of the regular season last year.  While this doesn’t guarantee that we have caught every trade, free agent move or player being waived; we are hoping that the majority of these type of transactions were captured in the system.

Some may like the baseline projections more than the final version.  I read one review of MORPS in 2014 that criticized the fact that we took the time to model anticipate plate appearances and batters faced for each team before releasing our final projections.  They didn’t consider that process “scientific”.   Our perspective is that the modeling allows us to adjust the ratios between each stat and plate appearance or batter faced to account for situations that weren’t present the year before.  This could be a player being part of a platoon when they played the position full-time the year before.  It could be a reduction in playing time due to the appearance of a blockbuster free agent or anticipated rookie hitting the big leagues.  It could also be a pitcher coming back from Tommy John surgery after being out of the game for over a year.  Regardless of the situation, we believe that the modeling of plate appearances and batters faced for each team adds significant value to MORPS projections.  This view is supported by our #1 ranking in 2014 for player projections using root mean square error (RMSE).  If you still doubt our ability to accurately model these situations or you have an early fantasy draft and need something now, you’re in luck.  You can use our baseline projections.

So…. without further ado, we present the 2016 MORPS Baseline Projections.   The Batting and Pitching projections are available in excel and PDF formats.  Follow the links below to download your copy.

2016 MORPS Batting Projections Baseline (XLS)

2016 MORPS Batting Projections Baseline (PDF)

2016 MORPS Pitching Projections Baseline (XLS)

2016 MORPS Pitching Projections Baseline (PDF)

 

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 re-sort the XLS spreadsheet in RC order for batters and OERV order for pitchers. Play Ball!

2015 Year in Review

Each year we take a moment to review our projections against the actual season results. First lets look at the team projections.  We definitely missed on the Kansas City Royals and their World Series win.   On the positive side, we did predict playoff runs for the Mets, Cardinals, Dodgers, Pirates and Blue Jays.  Our only miss in the NL was the Cubs over the Nationals.  The AL is another story.  In addition to the Royals, we also missed on the Astros, Rangers, and Yankees.  Predicting 50% of the playoff participants isn’t bad considering the number of roster changes that happen during the course of the season.

For individual projections, we were pleasantly surprised that MORPS  was the number one overall projection system in terms of Root Mean Square Error (RMSE) according to The Baseball Projection Project.   The 2014 results were published in March on Fangraphs – click here.   Based upon improvements implemented for 2015, our hope is that those results are replicated when 2015 results are published later this year.  For fantasy owners, this means that MORPS has the lowest error rate of all published projection systems on the market.  A lower error rate means that you can rely on the order that players are ranked within the MORPS projection system.

Overall predictive capability was another rating category tackled by The Baseball Projection Project.  MORPS didn’t do as well in this category.  Upon analysis, this is due to the regression to the mean built into the MORPS engine.  This doesn’t have a huge impact on established players.  It does have an impact on players with three or less years of experience or players returning from lengthy injuries.   We’ll be looking into this further to determine if there is a way to compete effectively in both categories effectively in the future.

Going into 2016, we are confident that our free projection system stacks up quite well with all of the systems out there.  This includes those that cost quite a bit of money to access.

2015 MORPS Team Projections

MORPS 2015 team projections are finished and posted below.  2014 team projections only picked 40% of the playoff teams which is worse than past years.  Teams like Baltimore and San Francisco were surprises while Texas and Colorado were major disappointments.  Between 2013 and 2010, MORPS team projections averaged 73%.  We are hoping to get back on the winning track this year.

This year’s team projections are as follows:

American League

2014 AL East

Wins

Losses

Boston

88

74

Toronto

88

74

Tampa Bay

82

80

New York

78

84

Baltimore

75

87

2014 AL Central

Wins

Losses

Detroit

88

74

Cleveland

83

79

Chicago

83

79

Kansas City

80

82

Minnesota

72

90

2014 AL West

Wins

Losses

Seattle

89

73

Los Angeles

87

75

Texas

77

85

Oakland

76

86

Houston

72

90

 

National League

2014 NL East

Wins

Losses

Washington

91

71

New York

83

79

Miami

79

83

Atlanta

77

85

Philadelphia

74

88

2014 NL Central

Wins

Losses

Saint Louis

85

77

Pittsburgh

84

78

Chicago

82

80

Milwaukee

81

81

Cincinnati

75

87

2014 NL West

Wins

Losses

Los Angeles

94

68

San Francisco

80

82

Arizona

79

83

San Diego

77

85

Colorado

73

89

The Division winners in the NL are Washington, Saint Louis and Los Angeles with Pittsburgh and New York slipping in as the wild card teams.  Yes, I know – I just predicated the Mets to make the playoffs – go figure.  The American League Division winners will be Boston, Detroit and Seattle with Toronto and Los Angeles as the wild card teams.

While the team with the most wins don’t always do that well in the playoffs, such distinctions can’t be made with a projection system built around “Runs Created” and “Runs Allowed”.  However, “Runs Created” and “Runs Allowed” do not always translate into the same number of wins if one team plays in a tougher division than another.  MORPS is projecting an AL championship between Boston and Toronto with Boston going to the world series.  In the National League it will be Los Angeles versus Washington with Los Angeles going to the world series.  MORPS projects that the Dodgers will win the series in 6 games.

Those that want more information on the projection methodology can click here.

As always, feel free to post your comments.

2015 MORPS Projections

2015 MORPS projections are ready.  Unlike the baseline projections published several weeks ago, these projections include all players projected to win a MLB roster spot on opening day.  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.

2015 MORPS Pitching Projections 20150331 (XLS)

2015 MORPS Pitching Projections 20150331 (PDF)

2015 MORPS Batting Projections 20150331 (XLS)

2015 MORPS Batting Projections 20150331 (PDF)

Team projections for 2015 will be posted within the next week.  Unfortunately, I will not have time this year to post an update to the roto draft tool.  Last year’s tool is still available on this site.  If someone wants to take the initiative to update the tool with this year’s projections, I would be happy to post your updated on the site.

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.

Play Ball!

2015 MORPS Baseline Projections

Back by popular demand in 2015 – MORPS baseline projections.

In 2014 I published a set of Baseline projections.  These projections used all the models we have put together over the years for projecting player performance.   This means that the projections are still based on four years of data, positional mean regression, etc.  However, they do not account for a player changing positions, reductions in playing time, new players to the big leagues, etc.  Unlike last year, we did enter all MLB player transactions into system since the end of the season last year.  While this doesn’t guarantee that we have caught every trade, free agent move or player being waived; we are hoping that the majority of these type of transactions were captured in the system.

Some may like the baseline projections more than the final version.  I read one review of MORPS last year that criticized the fact that we took the time to model anticipate plate appearances and batters faced for each team before releasing our final projections.  They didn’t consider that process “scientific”.   Our perspective is that the modeling allows us to adjust the ratios between each stat and plate appearance or batter faced to account for situations that weren’t present the year before.  This could be a player being part of a platoon when they played the position full-time the year before.  It could be a reduction in playing time due to the appearance of a blockbuster free agent or anticipated rookie hitting the big leagues.  It could also be a pitcher coming back from Tommy John surgery after being out of the game for over a year.  Regardless of the situation, we believe that the modeling of plate appearances and batters faced for each team adds significant value to MORPS projections.  If you doubt our ability to accurately model these situations or you have an early fantasy draft and need something now, you’re in luck.  You can use our baseline projections.

So…. Drum roll please.  Without further ado, we present the 2015 MORPS Baseline Projections.   The Batting and Pitching projections are available in excel and PDF formats.  Follow the links below to download your copy.

2015 MORPS Batting Projections Baseline (XLS)

2015 MORPS Batting Projections Baseline (PDF)

2015 MORPS Pitching Projections Baseline (XLS)

2015 MORPS Pitching Projections Baseline (PDF)

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 re-sort the XLS spreadsheet in RC order for batters and OERV order for pitchers. Play Ball!

2015 MORPS Projections

We are analyzing Stats and entering MLB off-season transactions into the model.   2015 MORPS Projections will be ready soon.  Stay tuned for more updates.

Final 2014 MORPS Projection Updates

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:

2014 MORPS Batting Projections 20140327 (XLS)

2014 MORPS Batting Projections 20140327 (PDF)

2014 MORPS Pitching Projections 20140327 (XLS)

2014 MORPS Pitching Projections 20140327 (PDF)

Feel free to leave comments or suggestions.

2014 Updates for MORPS Projections

Spring Training always adds unexpected twists for projection systems.  This year is no different.  Injuries, position battle updates, and unexpected player transactions lead to changes in player projections.  During the year, this simply leads to variance from projected player performance.  During Spring Training, projection systems have a chance to make last-minute corrections to account for all these changes.

MORPS updates for pitchers and batters are as follows:

2014 MORPS Batting Projections 20140313 (XLS)

2014 MORPS Batting Projections 20140313 (PDF)

2014 MORPS Pitching Projections 20140313 (XLS)

2014 MORPS Pitching Projections 20140313 (PDF)

Feel free to leave comments or suggestions.

Obie

2014 MORPS Roto Draft Tool

I came across an excel tool two years ago from Razzball that automated much of the draft process for ROTO leagues.  I modified it with MORPS projections and added a bit more functionality.  It worked well for my ROTO drafts the last two years.  Thus, I decided to use it again this year.  I also decided to share the modified tool this year with MORPS followers.

2014 MORPS Roto Draft Tool

Take time to check the instructions page.  It highlights what needs done to complete your preparation.  The User Input page allows you to customize the tool for your own league, goals, etc.  The only other page you will need to alter in any way is the Players page.  During the draft, you update players taken on this page with a drop down team selection that uses the teams you entered on the User Input page.  Players are automatically marked as taken in the dashboard by stat and the dashboard by position.  This allows you to see next available players based upon position or any of the standard 5×5 roto stat categories.  The War Room is where all the player draft data is consolidated together to give you a running overview of your team and the other teams in your league.

Feel free to make suggestions for improvement.  Hopefully everyone else finds it as useful as I did with my own drafts.

2014 MORPS Projections

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.

2014 MORPS Batting Projections 20140227 (XLS)

2014 MORPS Batting Projections 20140227 (PDF)

2014 MORPS Pitching Projections 20140227 (XLS)

2014 MORPS Pitching Projections 20140227 (PDF)

Batting Projections

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.

Pitching Projections

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.

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