Tuesday, March 10, 2015
Exportable 2015 MLB Schedule
Something that is difficult to find on the internet is an excel download file of the 2015 MLB Schedule. I have taken the time to write a script that takes the 2015 MLB Schedule and converts it to an easy to use CSV file and uploaded it to google docs. The file is free to download and can be found at the following link.
Here is the format that the file is in
Game ID,Year,Month,Day,Time,Away,Home
1,2015,4,5,8:05 PM,Cardinals,Cubs
2,2015,4,6,1:05 PM,Blue Jays,Yankees
3,2015,4,6,1:08 PM,Twins,Tigers
4,2015,4,6,2:10 PM,Rockies,Brewers
5,2015,4,6,3:05 PM,Red Sox,Phillies
6,2015,4,6,3:10 PM,Orioles,Rays
7,2015,4,6,4:05 PM,Mets,Nationals
8,2015,4,6,4:10 PM,Braves,Marlins
9,2015,4,6,4:10 PM,White Sox,Royals
10,2015,4,6,4:10 PM,Angels,Mariners
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2426,2015,10,4,3:10 PM,Athletics,Mariners
2427,2015,10,4,3:10 PM,Padres,Dodgers
2428,2015,10,4,3:10 PM,Blue Jays,Rays
2429,2015,10,4,3:10 PM,Nationals,Mets
2430,2015,10,4,4:10 PM,Astros,D-backs
Please keep in mind that game times and dates will be changing due to rain and I will not be maintaining these changes.
Monday, March 02, 2015
Oakland Athletics - 2015 Most Optimal Lineups
There are many ways people attempt to determine the best batting order. Some people try to arrange high on base percentage people at the top of the lineup followed by sluggers and then the rest of the crew and slap on a pitcher batting 9th (NL Team) and you are good to go. Others try calculators where you enter in player stats and out pops the best lineups. These are all fun and probably get you part of the way there but they are in NO WAY scientific enough to make much of a claim to what the top lineups might be.
The best way (in my opinion) to determine which lineup is the best is to actually trot out every single lineup and see which one wins the most games. Of course you would have to hold the opponent constant, using the same starters, lineup and starting pitcher. How hard could that be to do? Let's see, with nine batters in a lineup you would only have 362,880 lineups to go through. How long could that take to play over 350,000 baseball games. You could probably filter those permutations down to 25,000 or so by limiting left handed batters from hitting back to back, limiting the pitcher (NL) to batting either 8th or 9th, plus a few other obvious things. Even if you could narrow things down to just two lineups, you would still need to play more than one game to determine which one was better. So how many samples/games would you need? 10? 20? or maybe an entire season (162) of games? No. You would need a lot more than that. Try tens of thousands just to separate the bad lineups from the good and then try a million or two to compare the best lineups.
Well, I think it is pretty impossible to play thousands of games one time or a couple of games a million times. Hypothetically, if one were able to play games with thousands of different lineups, thousands or millions of times against the exact same opponent then you would get a very good idea as to which lineups were the best. This is where simulation comes in handy. A simulator that could play actual baseball games, by actual baseball rules, taking into consideration the important facets of a real baseball game like speed, defense, pitchers getting tired the more pitches they throw, splits, hitter vs pitcher matchups and outcomes and throw in some good player projections like the ones available for free at Fangraphs and then maybe through the power of the computer you could plow through tens of thousands of likely lineups to determine the best ones.
Now, you would be able to test the synergy of batting certain groups of players next to each other. You would be able to experiment with various types of hitters hitting in different spots. In fact, you could just let the computer run through each lineup and let you know what the top ones were, even tabulating how many times each player showed up at each spot in the top lineups. Now you would have a good list of top lineups and be able to measure how many wins a manager might be leaving on the table by using the lineup(s) that he used. Wouldn't it be very worthwhile for a team to know what its best lineups might be? Of course it would, especially considering that on the free agent market one win (or WAR) is typically worth around $7M. For managers that might not want to hit certain batters in certain lineup spots for whatever reason, he could use the filtering option to only measure lineups that fit his parameters.
Well, now on to what my game simulator using Steamer hitting projections lists as the top fifty lineups for the 2015 Oakland Athletics. I only looked at lineups against a right handed starting pitcher and took the nine most likely starters from the list at the Roster Resource website and I have of course used their most common lineup as one of the many (10,000+) lineups that I am looking at. Along with the top fifty lineups, there is a table showing how many times each player shows up in each lineup spot and what the most common back to back slottings are as well as back to back to back slottings (think synergy here).
Summary:
The batting order frequency table tells a lot here. If you were to piece together a lineup from only the frequency table you would likely come up with what is the second ranked optimal lineup. The lineup listed from the Roster Resource website came in listed 34th. I've ran a few of these now for various teams and the Athletics seem to have a very balanced lineup with no one player way better than the others not causing much of a spread between the top lineups. I also purposely added a bad lineup to the bottom of the top 50 list just to see what the maximum spread for the team looks like. According to the simulator, there are not a lot of wins for the Athletics manager to leave on the table vs RHP compared to some of the other teams.
Top 50 Lineups (vs RHP)
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Batting Order Frequency Table
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Back to Back Frequency Leaders
Back To Back to Back Frequency Leaders
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.
The best way (in my opinion) to determine which lineup is the best is to actually trot out every single lineup and see which one wins the most games. Of course you would have to hold the opponent constant, using the same starters, lineup and starting pitcher. How hard could that be to do? Let's see, with nine batters in a lineup you would only have 362,880 lineups to go through. How long could that take to play over 350,000 baseball games. You could probably filter those permutations down to 25,000 or so by limiting left handed batters from hitting back to back, limiting the pitcher (NL) to batting either 8th or 9th, plus a few other obvious things. Even if you could narrow things down to just two lineups, you would still need to play more than one game to determine which one was better. So how many samples/games would you need? 10? 20? or maybe an entire season (162) of games? No. You would need a lot more than that. Try tens of thousands just to separate the bad lineups from the good and then try a million or two to compare the best lineups.
Well, I think it is pretty impossible to play thousands of games one time or a couple of games a million times. Hypothetically, if one were able to play games with thousands of different lineups, thousands or millions of times against the exact same opponent then you would get a very good idea as to which lineups were the best. This is where simulation comes in handy. A simulator that could play actual baseball games, by actual baseball rules, taking into consideration the important facets of a real baseball game like speed, defense, pitchers getting tired the more pitches they throw, splits, hitter vs pitcher matchups and outcomes and throw in some good player projections like the ones available for free at Fangraphs and then maybe through the power of the computer you could plow through tens of thousands of likely lineups to determine the best ones.
Now, you would be able to test the synergy of batting certain groups of players next to each other. You would be able to experiment with various types of hitters hitting in different spots. In fact, you could just let the computer run through each lineup and let you know what the top ones were, even tabulating how many times each player showed up at each spot in the top lineups. Now you would have a good list of top lineups and be able to measure how many wins a manager might be leaving on the table by using the lineup(s) that he used. Wouldn't it be very worthwhile for a team to know what its best lineups might be? Of course it would, especially considering that on the free agent market one win (or WAR) is typically worth around $7M. For managers that might not want to hit certain batters in certain lineup spots for whatever reason, he could use the filtering option to only measure lineups that fit his parameters.
Well, now on to what my game simulator using Steamer hitting projections lists as the top fifty lineups for the 2015 Oakland Athletics. I only looked at lineups against a right handed starting pitcher and took the nine most likely starters from the list at the Roster Resource website and I have of course used their most common lineup as one of the many (10,000+) lineups that I am looking at. Along with the top fifty lineups, there is a table showing how many times each player shows up in each lineup spot and what the most common back to back slottings are as well as back to back to back slottings (think synergy here).
Summary:
The batting order frequency table tells a lot here. If you were to piece together a lineup from only the frequency table you would likely come up with what is the second ranked optimal lineup. The lineup listed from the Roster Resource website came in listed 34th. I've ran a few of these now for various teams and the Athletics seem to have a very balanced lineup with no one player way better than the others not causing much of a spread between the top lineups. I also purposely added a bad lineup to the bottom of the top 50 list just to see what the maximum spread for the team looks like. According to the simulator, there are not a lot of wins for the Athletics manager to leave on the table vs RHP compared to some of the other teams.
Top 50 Lineups (vs RHP)
| Rank | Lineup | Wins/162 Games Behind |
|---|---|---|
| 1 | Zobrist-Reddick-Lawrie-Davis-Crisp-Semien-Vogt-Butler-Fuld | 0 |
| 2 | Crisp-Reddick-Lawrie-Davis-Zobrist-Vogt-Semien-Butler-Fuld | 0.001 |
| 3 | Reddick-Crisp-Lawrie-Davis-Zobrist-Vogt-Semien-Fuld-Butler | 0.016 |
| 4 | Crisp-Vogt-Lawrie-Davis-Zobrist-Reddick-Semien-Butler-Fuld | 0.042 |
| 5 | Zobrist-Fuld-Lawrie-Reddick-Crisp-Vogt-Semien-Butler-Davis | 0.067 |
| 6 | Crisp-Vogt-Lawrie-Davis-Zobrist-Semien-Fuld-Butler-Reddick | 0.093 |
| 7 | Fuld-Crisp-Butler-Davis-Zobrist-Reddick-Lawrie-Vogt-Semien | 0.094 |
| 8 | Davis-Zobrist-Lawrie-Reddick-Crisp-Vogt-Semien-Fuld-Butler | 0.103 |
| 9 | Reddick-Semien-Lawrie-Davis-Crisp-Fuld-Zobrist-Vogt-Butler | 0.107 |
| 10 | Zobrist-Reddick-Lawrie-Davis-Semien-Crisp-Vogt-Butler-Fuld | 0.108 |
| 11 | Lawrie-Crisp-Davis-Zobrist-Reddick-Semien-Vogt-Butler-Fuld | 0.108 |
| 12 | Semien-Davis-Lawrie-Reddick-Crisp-Fuld-Zobrist-Vogt-Butler | 0.109 |
| 13 | Zobrist-Reddick-Lawrie-Davis-Crisp-Fuld-Butler-Vogt-Semien | 0.117 |
| 14 | Crisp-Reddick-Lawrie-Davis-Semien-Zobrist-Fuld-Butler-Vogt | 0.123 |
| 15 | Zobrist-Crisp-Reddick-Lawrie-Davis-Semien-Fuld-Butler-Vogt | 0.14 |
| 16 | Semien-Davis-Lawrie-Reddick-Zobrist-Crisp-Vogt-Butler-Fuld | 0.141 |
| 17 | Semien-Fuld-Butler-Davis-Zobrist-Reddick-Lawrie-Crisp-Vogt | 0.146 |
| 18 | Zobrist-Reddick-Lawrie-Davis-Crisp-Vogt-Semien-Fuld-Butler | 0.146 |
| 19 | Reddick-Crisp-Davis-Zobrist-Lawrie-Vogt-Semien-Fuld-Butler | 0.152 |
| 20 | Fuld-Crisp-Butler-Davis-Semien-Reddick-Lawrie-Vogt-Zobrist | 0.156 |
| 21 | Zobrist-Fuld-Lawrie-Davis-Crisp-Vogt-Semien-Butler-Reddick | 0.156 |
| 22 | Reddick-Zobrist-Davis-Lawrie-Crisp-Vogt-Semien-Fuld-Butler | 0.159 |
| 23 | Crisp-Butler-Reddick-Lawrie-Davis-Semien-Vogt-Zobrist-Fuld | 0.175 |
| 24 | Reddick-Crisp-Davis-Lawrie-Zobrist-Vogt-Semien-Fuld-Butler | 0.181 |
| 25 | Fuld-Crisp-Lawrie-Davis-Zobrist-Reddick-Semien-Vogt-Butler | 0.191 |
| 26 | Reddick-Zobrist-Lawrie-Davis-Semien-Fuld-Crisp-Vogt-Butler | 0.192 |
| 27 | Crisp-Zobrist-Reddick-Lawrie-Davis-Semien-Fuld-Butler-Vogt | 0.192 |
| 28 | Crisp-Davis-Lawrie-Reddick-Zobrist-Vogt-Semien-Butler-Fuld | 0.195 |
| 29 | Crisp-Fuld-Lawrie-Reddick-Zobrist-Semien-Vogt-Butler-Davis | 0.204 |
| 30 | Crisp-Semien-Davis-Lawrie-Reddick-Zobrist-Fuld-Butler-Vogt | 0.209 |
| 31 | Crisp-Fuld-Lawrie-Davis-Zobrist-Reddick-Butler-Semien-Vogt | 0.210 |
| 32 | Crisp-Zobrist-Davis-Lawrie-Fuld-Semien-Vogt-Butler-Reddick | 0.213 |
| 33 | Semien-Fuld-Lawrie-Reddick-Zobrist-Crisp-Vogt-Butler-Davis | 0.214 |
| 34 | Reddick-Crisp-Davis-Zobrist-Vogt-Lawrie-Semien-Fuld-Butler | 0.218 |
| 35 | Crisp-Zobrist-Reddick-Butler-Davis-Lawrie-Vogt-Semien-Fuld | 0.221 |
| 36 | Reddick-Zobrist-Davis-Lawrie-Fuld-Semien-Crisp-Vogt-Butler | 0.222 |
| 37 | Crisp-Davis-Butler-Reddick-Zobrist-Lawrie-Vogt-Semien-Fuld | 0.236 |
| 38 | Semien-Davis-Zobrist-Reddick-Crisp-Vogt-Lawrie-Fuld-Butler | 0.238 |
| 39 | Crisp-Vogt-Lawrie-Davis-Semien-Butler-Reddick-Zobrist-Fuld | 0.242 |
| 40 | Crisp-Zobrist-Reddick-Lawrie-Vogt-Semien-Fuld-Butler-Davis | 0.244 |
| 41 | Zobrist-Reddick-Lawrie-Davis-Crisp-Fuld-Butler-Semien-Vogt | 0.248 |
| 42 | Crisp-Butler-Reddick-Lawrie-Davis-Zobrist-Vogt-Semien-Fuld | 0.257 |
| 43 | Lawrie-Fuld-Butler-Davis-Crisp-Zobrist-Vogt-Semien-Reddick | 0.258 |
| 44 | Crisp-Reddick-Lawrie-Davis-Semien-Fuld-Butler-Zobrist-Vogt | 0.260 |
| 45 | Davis-Zobrist-Reddick-Lawrie-Fuld-Crisp-Vogt-Semien-Butler | 0.263 |
| 46 | Crisp-Fuld-Butler-Davis-Lawrie-Reddick-Semien-Vogt-Zobrist | 0.267 |
| 47 | Crisp-Reddick-Butler-Davis-Semien-Zobrist-Fuld-Lawrie-Vogt | 0.283 |
| 48 | Fuld-Semien-Lawrie-Davis-Crisp-Reddick-Zobrist-Vogt-Butler | 0.284 |
| 49 | Crisp-Vogt-Zobrist-Davis-Lawrie-Reddick-Semien-Butler-Fuld | 0.294 |
| 50 | Crisp-Reddick-Butler-Davis-Zobrist-Lawrie-Vogt-Semien-Fuld | 0.294 |
| BAD | Vogt-Butler-Fuld-Crisp-Semien-Davis-Zobrist-Reddick-Lawrie | 1.419 |
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Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Crisp | 21 | 9 | 0 | 0 | 13 | 4 | 2 | 1 | 0 |
| Reddick | 8 | 10 | 7 | 9 | 2 | 9 | 1 | 0 | 4 |
| Lawrie | 2 | 0 | 25 | 11 | 3 | 4 | 4 | 1 | 0 |
| Davis | 2 | 5 | 8 | 26 | 5 | 0 | 0 | 0 | 4 |
| Zobrist | 8 | 9 | 2 | 3 | 15 | 5 | 3 | 3 | 2 |
| Vogt | 0 | 4 | 0 | 0 | 2 | 11 | 14 | 10 | 9 |
| Semien | 5 | 3 | 0 | 0 | 7 | 10 | 15 | 8 | 2 |
| Butler | 0 | 2 | 8 | 1 | 0 | 1 | 4 | 19 | 15 |
| Fuld | 4 | 8 | 0 | 0 | 3 | 6 | 7 | 8 | 14 |
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Synergy
Back to Back Frequency Leaders
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 22 | Lawrie | Davis |
| 2 | 20 | Vogt | Semien |
| 3 | 20 | Semien | Fuld |
| 4 | 20 | Fuld | Butler |
| 5 | 18 | Reddick | Lawrie |
| 6 | 17 | Crisp | Vogt |
| 7 | 17 | Davis | Zobrist |
| 8 | 16 | Zobrist | Reddick |
| 9 | 15 | Butler | Reddick |
| 10 | 15 | Fuld | Crisp |
| 11 | 14 | Butler | Davis |
| 12 | 13 | Vogt | Butler |
| 13 | 12 | Reddick | Zobrist |
| 14 | 11 | Davis | Lawrie |
| 15 | 11 | Davis | Semien |
| 16 | 11 | Zobrist | Vogt |
| 17 | 10 | Reddick | Crisp |
| 18 | 10 | Lawrie | Reddick |
| 19 | 10 | Davis | Crisp |
| 20 | 10 | Butler | Fuld |
Back To Back to Back Frequency Leaders
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 13 | Vogt | Semien | Fuld |
| 2 | 13 | Semien | Fuld | Butler |
| 3 | 12 | Reddick | Lawrie | Davis |
| 4 | 10 | Zobrist | Reddick | Lawrie |
| 5 | 8 | Lawrie | Davis | Semien |
| 6 | 8 | Davis | Zobrist | Reddick |
| 7 | 7 | Crisp | Vogt | Semien |
| 8 | 7 | Lawrie | Davis | Crisp |
| 9 | 7 | Lawrie | Davis | Zobrist |
| 10 | 6 | Lawrie | Vogt | Semien |
| 11 | 6 | Davis | Lawrie | Reddick |
| 12 | 6 | Zobrist | Vogt | Semien |
| 13 | 6 | Vogt | Butler | Fuld |
| 14 | 6 | Semien | Fuld | Crisp |
| 15 | 6 | Butler | Reddick | Crisp |
| 16 | 6 | Butler | Reddick | Zobrist |
| 17 | 6 | Butler | Davis | Zobrist |
| 18 | 6 | Fuld | Butler | Reddick |
| 19 | 5 | Crisp | Vogt | Butler |
| 20 | 5 | Lawrie | Reddick | Zobrist |
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Thursday, February 26, 2015
LA Dodgers 2015 Preview
As the 2015 Major League Baseball season approaches, signs point to this year as a good season to be a LA Dodgers fan. The organization made the move to bring in former Oakland Athletics’ GM, Farhan Zaidi back in November, and are primed for another run this coming season.
The new general manager, along with the new president of baseball operations, Andrew Friedman have had a very active off season thus far for their new club. After letting disgruntled shortstop Hanley Ramirez leave in free agency, they also agreed to pay $30 million of Matt Kemp’s salary in order to send the temperamental outfielder south to the San Diego Padres. In addition to those moves, they also traded for shortstop Jimmy Rollins and second baseman Howie Kendrick, two solid veterans with high character qualities that will pay dividends in the locker room. They also made a couple moves that many considered questionable, like the signing of Brandon McCarthy and Brett Anderson, who are both talented pitchers but who have struggled with injuries throughout most their careers. Regardless, both should help bolster the back end of the Dodgers rotation this season.
Besides the new additions, LA is also returning some of the biggest star players in the game, Clayton Kershaw and Yasiel Puig. Kershaw is well on his way to becoming a living legend as he became only the third starting pitcher in the history of the game to lead their league in ERA for four straight seasons, and there’s little reason to doubt that he can make this season his fifth straight in leading the league in ERA.
Backing up Kershaw in the outfield is arguably the most dynamic player in the game today, Yasiel Puig. The exciting and explosive Cuban-born player continues to be one of the most entertaining players in the league. With his rocket arm that can throw runners out at home from the warning track, his blazing speed which makes any gap single into a potential double, and his acrobatic catches he makes on a routine basis, Puig is quickly becoming one of the best all-around players in the game.
With some new faces running the show this season for the Dodgers, and some solid additions to their club, the Dodgers are once again expected to be right in the thick of things come playoff time of the 2015 baseball season. Plenty of story lines to look forward to this year, especially Kershaw’s attempt to go for his fifth straight season leading the league in ERA. It’s a great year to be a fan of LA Dodgers baseball, and we look forward to another successful campaign for the upcoming season.
This article was brought you by the handicapping experts at Sports Information Traders. For 2015 MLB Picks and predictions as well as sports betting tips to help you get through this years Major League Baseball season.
The new general manager, along with the new president of baseball operations, Andrew Friedman have had a very active off season thus far for their new club. After letting disgruntled shortstop Hanley Ramirez leave in free agency, they also agreed to pay $30 million of Matt Kemp’s salary in order to send the temperamental outfielder south to the San Diego Padres. In addition to those moves, they also traded for shortstop Jimmy Rollins and second baseman Howie Kendrick, two solid veterans with high character qualities that will pay dividends in the locker room. They also made a couple moves that many considered questionable, like the signing of Brandon McCarthy and Brett Anderson, who are both talented pitchers but who have struggled with injuries throughout most their careers. Regardless, both should help bolster the back end of the Dodgers rotation this season.
Besides the new additions, LA is also returning some of the biggest star players in the game, Clayton Kershaw and Yasiel Puig. Kershaw is well on his way to becoming a living legend as he became only the third starting pitcher in the history of the game to lead their league in ERA for four straight seasons, and there’s little reason to doubt that he can make this season his fifth straight in leading the league in ERA.
Backing up Kershaw in the outfield is arguably the most dynamic player in the game today, Yasiel Puig. The exciting and explosive Cuban-born player continues to be one of the most entertaining players in the league. With his rocket arm that can throw runners out at home from the warning track, his blazing speed which makes any gap single into a potential double, and his acrobatic catches he makes on a routine basis, Puig is quickly becoming one of the best all-around players in the game.
With some new faces running the show this season for the Dodgers, and some solid additions to their club, the Dodgers are once again expected to be right in the thick of things come playoff time of the 2015 baseball season. Plenty of story lines to look forward to this year, especially Kershaw’s attempt to go for his fifth straight season leading the league in ERA. It’s a great year to be a fan of LA Dodgers baseball, and we look forward to another successful campaign for the upcoming season.
This article was brought you by the handicapping experts at Sports Information Traders. For 2015 MLB Picks and predictions as well as sports betting tips to help you get through this years Major League Baseball season.
Wednesday, February 25, 2015
Miami Marlins - 2015 Most Optimal Lineups
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Miami Marlins (vs RHP). I started out with 15,000 almost random lineups and I slowly widdled it down to the top 50 lineups. Almost random, because I filtered out some obvious things like batting Stanton 8th or 9th or Dee Gordon cleanup etc... For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within 0.85 wins per 162 games which is a pretty wide range for a top 50 lineup list. When you start nearing a full win differential with the top lineup then you definitely have problems and the projected lineup from MLB Depth Charts finished 1.65 wins/162 games behind (not good). You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. The simulator is a program that I wrote in C/C++ and I have back tested it against Vegas odds in the past to make sure it is good. The program plays actual games, with actual baseball rules and takes pretty much everything you can think of into consideration. This exercise is NOT trying to project what lineups the Marlins manager might or will actually use it is just outputting what it thinks are the best lineups. Once down to the top fifty lineups, I simulated each lineup 2 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 50 Lineups
Batting Order Frequency Table
20 Most Common Back to Back Occurrences
20 Most Common Back to Back to Back Occurrences
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.
I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Miami Marlins (vs RHP). I started out with 15,000 almost random lineups and I slowly widdled it down to the top 50 lineups. Almost random, because I filtered out some obvious things like batting Stanton 8th or 9th or Dee Gordon cleanup etc... For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within 0.85 wins per 162 games which is a pretty wide range for a top 50 lineup list. When you start nearing a full win differential with the top lineup then you definitely have problems and the projected lineup from MLB Depth Charts finished 1.65 wins/162 games behind (not good). You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. The simulator is a program that I wrote in C/C++ and I have back tested it against Vegas odds in the past to make sure it is good. The program plays actual games, with actual baseball rules and takes pretty much everything you can think of into consideration. This exercise is NOT trying to project what lineups the Marlins manager might or will actually use it is just outputting what it thinks are the best lineups. Once down to the top fifty lineups, I simulated each lineup 2 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 50 Lineups
| Rank | Lineup | Wins/162 Games Behind |
|---|---|---|
| 1 | Yelich-Gordon-Prado-Stanton-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0 |
| 2 | Gordon-Yelich-Prado-Stanton-Morse-Ozuna-Salta-Pitcher-Hechavarria | 0.232 |
| 3 | Yelich-Gordon-Prado-Stanton-Morse-Ozuna-Salta-Pitcher-Hechavarria | 0.250 |
| 4 | Gordon-Yelich-Prado-Stanton-Ozuna-Hechavarria-Morse-Salta-Pitcher | 0.308 |
| 5 | Gordon-Yelich-Prado-Ozuna-Stanton-Morse-Salta-Pitcher-Hechavarria | 0.359 |
| 6 | Yelich-Gordon-Prado-Stanton-Ozuna-Morse-Hechavarria-Salta-Pitcher | 0.374 |
| 7 | Yelich-Gordon-Prado-Stanton-Ozuna-Hechavarria-Salta-Pitcher-Morse | 0.384 |
| 8 | Yelich-Gordon-Prado-Ozuna-Stanton-Morse-Salta-Pitcher-Hechavarria | 0.386 |
| 9 | Gordon-Yelich-Stanton-Prado-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0.392 |
| 10 | Yelich-Gordon-Stanton-Prado-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0.438 |
| 11 | Gordon-Yelich-Prado-Stanton-Ozuna-Morse-Hechavarria-Salta-Pitcher | 0.443 |
| 12 | Gordon-Yelich-Prado-Stanton-Ozuna-Hechavarria-Salta-Pitcher-Morse | 0.448 |
| 13 | Ozuna-Gordon-Prado-Stanton-Yelich-Hechavarria-Morse-Salta-Pitcher | 0.491 |
| 14 | Yelich-Gordon-Prado-Morse-Stanton-Ozuna-Salta-Pitcher-Hechavarria | 0.498 |
| 15 | Gordon-Prado-Yelich-Stanton-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0.525 |
| 16 | Gordon-Yelich-Prado-Morse-Stanton-Ozuna-Salta-Pitcher-Hechavarria | 0.541 |
| 17 | Yelich-Gordon-Stanton-Prado-Morse-Ozuna-Salta-Pitcher-Hechavarria | 0.543 |
| 18 | Gordon-Hechavarria-Prado-Stanton-Yelich-Ozuna-Morse-Salta-Pitcher | 0.546 |
| 19 | Yelich-Gordon-Stanton-Prado-Ozuna-Hechavarria-Morse-Salta-Pitcher | 0.553 |
| 20 | Yelich-Gordon-Stanton-Prado-Ozuna-Hechavarria-Salta-Pitcher-Morse | 0.574 |
| 21 | Gordon-Prado-Stanton-Yelich-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0.584 |
| 22 | Gordon-Ozuna-Prado-Stanton-Yelich-Morse-Salta-Pitcher-Hechavarria | 0.584 |
| 23 | Yelich-Gordon-Prado-Stanton-Morse-Hechavarria-Ozuna-Salta-Pitcher | 0.594 |
| 24 | Gordon-Prado-Stanton-Ozuna-Yelich-Morse-Salta-Pitcher-Hechavarria | 0.605 |
| 25 | Gordon-Yelich-Ozuna-Prado-Stanton-Morse-Salta-Pitcher-Hechavarria | 0.613 |
| 26 | Gordon-Prado-Ozuna-Stanton-Yelich-Morse-Salta-Pitcher-Hechavarria | 0.633 |
| 27 | Gordon-Yelich-Stanton-Prado-Ozuna-Hechavarria-Morse-Salta-Pitcher | 0.641 |
| 28 | Gordon-Yelich-Morse-Prado-Stanton-Ozuna-Salta-Pitcher-Hechavarria | 0.642 |
| 29 | Gordon-Yelich-Prado-Stanton-Morse-Ozuna-Hechavarria-Salta-Pitcher | 0.648 |
| 30 | Gordon-Prado-Yelich-Stanton-Morse-Ozuna-Salta-Pitcher-Hechavarria | 0.652 |
| 31 | Ozuna-Gordon-Prado-Stanton-Yelich-Morse-Hechavarria-Salta-Pitcher | 0.653 |
| 32 | Prado-Gordon-Yelich-Stanton-Ozuna-Morse-Salta-Pitcher-Hechavarria | 0.659 |
| 33 | Gordon-Hechavarria-Prado-Stanton-Yelich-Ozuna-Salta-Pitcher-Morse | 0.674 |
| 34 | Yelich-Gordon-Stanton-Prado-Ozuna-Morse-Hechavarria-Salta-Pitcher | 0.678 |
| 35 | Yelich-Gordon-Ozuna-Prado-Stanton-Morse-Salta-Pitcher-Hechavarria | 0.685 |
| 36 | Gordon-Morse-Prado-Stanton-Yelich-Ozuna-Hechavarria-Salta-Pitcher | 0.688 |
| 37 | Gordon-Yelich-Prado-Stanton-Morse-Hechavarria-Salta-Pitcher-Ozuna | 0.704 |
| 38 | Ozuna-Gordon-Prado-Yelich-Stanton-Morse-Salta-Pitcher-Hechavarria | 0.723 |
| 39 | Ozuna-Hechavarria-Prado-Stanton-Yelich-Gordon-Morse-Salta-Pitcher | 0.725 |
| 40 | Gordon-Morse-Prado-Stanton-Yelich-Ozuna-Salta-Pitcher-Hechavarria | 0.727 |
| 41 | Gordon-Yelich-Stanton-Prado-Ozuna-Morse-Hechavarria-Salta-Pitcher | 0.735 |
| 42 | Yelich-Gordon-Prado-Stanton-Ozuna-Morse-Hechavarria-Pitcher-Salta | 0.741 |
| 43 | Gordon-Prado-Morse-Stanton-Yelich-Ozuna-Salta-Pitcher-Hechavarria | 0.758 |
| 44 | Gordon-Yelich-Stanton-Ozuna-Prado-Morse-Salta-Pitcher-Hechavarria | 0.770 |
| 45 | Yelich-Gordon-Prado-Ozuna-Morse-Stanton-Salta-Pitcher-Hechavarria | 0.771 |
| 46 | Prado-Gordon-Stanton-Ozuna-Yelich-Morse-Salta-Pitcher-Hechavarria | 0.775 |
| 47 | Yelich-Gordon-Morse-Stanton-Prado-Ozuna-Salta-Pitcher-Hechavarria | 0.775 |
| 48 | Yelich-Gordon-Prado-Stanton-Ozuna-Salta-Morse-Pitcher-Hechavarria | 0.799 |
| 49 | Gordon-Yelich-Prado-Morse-Ozuna-Stanton-Salta-Pitcher-Hechavarria | 0.810 |
| 50 | Gordon-Hechavarria-Prado-Stanton-Ozuna-Yelich-Morse-Salta-Pitcher | 0.855 |
| MLBDC | Gordon-Yelich-Stanton-Morse-Prado-Ozuna-Salta-Hechavarria-pitcher | 1.648 |
| BAD | Salta-Hechavarria-Morse-Gordon-Ozuna-Prado-Yelich-Stanton-Pitcher | 4.400 |
Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Gordon | 27 | 22 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| Yelich | 17 | 15 | 3 | 2 | 12 | 1 | 0 | 0 | 0 |
| Prado | 2 | 6 | 29 | 11 | 2 | 0 | 0 | 0 | 0 |
| Stanton | 0 | 0 | 12 | 28 | 8 | 2 | 0 | 0 | 0 |
| Ozuna | 4 | 1 | 3 | 6 | 20 | 14 | 1 | 0 | 1 |
| Morse | 0 | 2 | 3 | 3 | 8 | 22 | 8 | 0 | 4 |
| Salta | 0 | 0 | 0 | 0 | 0 | 1 | 33 | 15 | 1 |
| Hechavarria | 0 | 4 | 0 | 0 | 0 | 9 | 8 | 0 | 29 |
| Pitcher | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 35 | 15 |
Synergy
20 Most Common Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 48 | Salta | Pitcher |
| 2 | 29 | Pitcher | Hechavarria |
| 3 | 27 | Prado | Stanton |
| 4 | 23 | Morse | Salta |
| 5 | 19 | Gordon | Prado |
| 6 | 18 | Yelich | Gordon |
| 7 | 17 | Stanton | Ozuna |
| 8 | 16 | Gordon | Yelich |
| 9 | 16 | Hechavarria | Gordon |
| 10 | 13 | Ozuna | Morse |
| 11 | 13 | Ozuna | Salta |
| 12 | 12 | Prado | Ozuna |
| 13 | 11 | Stanton | Yelich |
| 14 | 11 | Stanton | Morse |
| 15 | 11 | Hechavarria | Salta |
| 16 | 10 | Hechavarria | Yelich |
| 17 | 9 | Yelich | Prado |
| 18 | 9 | Stanton | Prado |
| 19 | 9 | Ozuna | Hechavarria |
| 20 | 8 | Yelich | Stanton |
| 20 | 8 | Morse | Hechavarria |
| 20 | 8 | Pitcher | Gordon |
20 Most Common Back to Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 28 | Salta | Pitcher | Hechavarria |
| 2 | 23 | Morse | Salta | Pitcher |
| 3 | 16 | Pitcher | Hechavarria | Gordon |
| 4 | 12 | Ozuna | Salta | Pitcher |
| 5 | 11 | Gordon | Prado | Stanton |
| 6 | 11 | Prado | Stanton | Ozuna |
| 7 | 11 | Hechavarria | Salta | Pitcher |
| 8 | 10 | Yelich | Gordon | Prado |
| 9 | 10 | Hechavarria | Yelich | Gordon |
| 10 | 10 | Pitcher | Hechavarria | Yelich |
| 11 | 9 | Gordon | Yelich | Prado |
| 12 | 9 | Prado | Stanton | Yelich |
| 13 | 8 | Stanton | Prado | Ozuna |
| 14 | 8 | Salta | Pitcher | Gordon |
| 15 | 8 | Hechavarria | Gordon | Yelich |
| 16 | 7 | Prado | Stanton | Morse |
| 17 | 7 | Ozuna | Morse | Salta |
| 18 | 6 | Yelich | Prado | Stanton |
| 19 | 6 | Stanton | Yelich | Ozuna |
| 20 | 6 | Stanton | Ozuna | Morse |
| 20 | 6 | Morse | Hechavarria | Salta |
| 20 | 6 | Hechavarria | Gordon | Prado |
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Tuesday, February 24, 2015
Dodgers Fantasy Outlook 2015
Author: Matt Smith
With one of the highest payrolls in the game, the Los Angeles Dodgers should be pretty competitive for the foreseeable future. However, for a franchise that has not won a World Series in over 25 years, being competitive is not enough. They have made some changes heading into the 2015 season to their roster, and the hope is that it is enough for regular and postseason success.
With one of the highest payrolls in the game, the Los Angeles Dodgers should be pretty competitive for the foreseeable future. However, for a franchise that has not won a World Series in over 25 years, being competitive is not enough. They have made some changes heading into the 2015 season to their roster, and the hope is that it is enough for regular and postseason success.
Even though they have a lot of fantasy baseball talent last season, nothing seemed to really click with the franchise consistently. They would play well in spurts, but then they would go on a cold streak. About the only dependable player on the roster was Clayton Kershaw, and ironically he became inconsistent as soon as the postseason began.
Andrew Feldman was brought in to help make better decisions in the front office for the Los Angeles Dodgers. With seemingly unlimited funds compared to what he was working with in Tampa Bay, it will be interesting to see what type of deals he pulls off in the future. Right away, he decided to go after veteran players who have championship pedigrees. Jimmy Rollins and Howie Kendrick can still provide value in fantasy baseball, but they will be just as important in the locker room.
Joc Pederson might not be new to the franchise, but he will now take over as the new everyday center fielder for the franchise. Many look at him as one of the top youngsters in the game, so he will need to hit the ground running in 2015. The franchise specifically made room for him by trading away some pretty decent talent, so it will be interesting to see what he does with a little bit more pressure on him.
Not only has losing been tough for the Los Angeles Dodgers in the postseason, but watching the San Francisco Giants win 3 World Series in the last 5 seasons stings. Hopefully, with some subtle moves, this team will be a bit better when the games matter most.
Sunday, February 15, 2015
Minnesota Twins - 2015 Most Optimal Lineups
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Minnesota Twins. I started out with 25,000 almost random lineups and I slowly widdled it down to the top 50 lineups. Almost random, because I filtered out some obvious things like batting Joe Mauer 8th or 9th etc... For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within 0.35 wins per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems and the projected lineup from MLB Depth Charts finished 0.59 wins/162 games behind (not bad). You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. This exercise is NOT trying to project what lineups the Twins manager might or will actually use it is just outputting what it thinks are the best lineups. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups. The Twins have two left handed batters in the starting nine that I used. For this exercise, I assumed that there was no restriction on batting the two left handed batters (Mauer, Arcia) back to back. Obviously, if you add that restriction then 33 of these 50 lineups would be different.
Top 50 Lineups (vs RHP)
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Batting Order Frequency Table
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Synergy
20 Most Common Back to Back Occurrences
20 Most Common Back to Back to Back Occurrences
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Minnesota Twins. I started out with 25,000 almost random lineups and I slowly widdled it down to the top 50 lineups. Almost random, because I filtered out some obvious things like batting Joe Mauer 8th or 9th etc... For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within 0.35 wins per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems and the projected lineup from MLB Depth Charts finished 0.59 wins/162 games behind (not bad). You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. This exercise is NOT trying to project what lineups the Twins manager might or will actually use it is just outputting what it thinks are the best lineups. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups. The Twins have two left handed batters in the starting nine that I used. For this exercise, I assumed that there was no restriction on batting the two left handed batters (Mauer, Arcia) back to back. Obviously, if you add that restriction then 33 of these 50 lineups would be different.
Top 50 Lineups (vs RHP)
| Rank | Lineup | Wins/162 Games Behind |
|---|---|---|
| 1 | Santana-Mauer-Arcia-Vargas-Hunter-Plouffe-Hicks-Suzuki-Dozier | 0 |
| 2 | Santana-Mauer-Vargas-Arcia-Hunter-Plouffe-Hicks-Suzuki-Dozier | 0.013 |
| 3 | Santana-Mauer-Arcia-Vargas-Hunter-Dozier-Plouffe-Suzuki-Hicks | 0.018 |
| 4 | Santana-Mauer-Vargas-Arcia-Dozier-Suzuki-Plouffe-Hicks-Hunter | 0.027 |
| 5 | Santana-Mauer-Vargas-Arcia-Plouffe-Hunter-Hicks-Suzuki-Dozier | 0.033 |
| 6 | Dozier-Santana-Mauer-Arcia-Vargas-Hicks-Suzuki-Plouffe-Hunter | 0.048 |
| 7 | Santana-Mauer-Arcia-Vargas-Dozier-Hunter-Plouffe-Hicks-Suzuki | 0.055 |
| 8 | Santana-Mauer-Arcia-Vargas-Plouffe-Hicks-Hunter-Dozier-Suzuki | 0.061 |
| 9 | Hunter-Santana-Mauer-Arcia-Vargas-Dozier-Plouffe-Suzuki-Hicks | 0.087 |
| 10 | Santana-Mauer-Arcia-Vargas-Hunter-Hicks-Plouffe-Suzuki-Dozier | 0.097 |
| 11 | Dozier-Santana-Mauer-Arcia-Vargas-Hunter-Hicks-Suzuki-Plouffe | 0.101 |
| 12 | Hicks-Santana-Mauer-Vargas-Arcia-Hunter-Plouffe-Dozier-Suzuki | 0.105 |
| 13 | Dozier-Santana-Mauer-Arcia-Vargas-Hicks-Hunter-Plouffe-Suzuki | 0.106 |
| 14 | Dozier-Santana-Mauer-Vargas-Arcia-Plouffe-Hunter-Suzuki-Hicks | 0.109 |
| 15 | Dozier-Mauer-Vargas-Arcia-Hicks-Santana-Suzuki-Hunter-Plouffe | 0.113 |
| 16 | Santana-Mauer-Arcia-Vargas-Plouffe-Dozier-Suzuki-Hicks-Hunter | 0.117 |
| 17 | Santana-Mauer-Vargas-Arcia-Hicks-Suzuki-Plouffe-Dozier-Hunter | 0.119 |
| 18 | Santana-Mauer-Arcia-Vargas-Hicks-Plouffe-Dozier-Suzuki-Hunter | 0.120 |
| 19 | Santana-Hunter-Vargas-Mauer-Arcia-Dozier-Plouffe-Suzuki-Hicks | 0.123 |
| 20 | Santana-Vargas-Mauer-Arcia-Hunter-Dozier-Suzuki-Plouffe-Hicks | 0.136 |
| 21 | Santana-Suzuki-Mauer-Arcia-Vargas-Plouffe-Hunter-Dozier-Hicks | 0.143 |
| 22 | Hunter-Santana-Mauer-Vargas-Arcia-Plouffe-Hicks-Dozier-Suzuki | 0.147 |
| 23 | Santana-Hunter-Vargas-Mauer-Arcia-Dozier-Plouffe-Hicks-Suzuki | 0.151 |
| 24 | Hunter-Santana-Vargas-Mauer-Arcia-Plouffe-Hicks-Suzuki-Dozier | 0.155 |
| 25 | Santana-Vargas-Mauer-Arcia-Hicks-Suzuki-Hunter-Plouffe-Dozier | 0.160 |
| 26 | Santana-Mauer-Vargas-Arcia-Hicks-Dozier-Suzuki-Plouffe-Hunter | 0.161 |
| 27 | Santana-Hunter-Vargas-Mauer-Arcia-Plouffe-Dozier-Suzuki-Hicks | 0.183 |
| 28 | Hicks-Mauer-Vargas-Arcia-Dozier-Santana-Suzuki-Plouffe-Hunter | 0.186 |
| 29 | Hunter-Santana-Vargas-Mauer-Arcia-Plouffe-Suzuki-Hicks-Dozier | 0.193 |
| 30 | Santana-Mauer-Vargas-Arcia-Dozier-Suzuki-Hicks-Plouffe-Hunter | 0.197 |
| 31 | Santana-Vargas-Mauer-Arcia-Dozier-Hicks-Hunter-Plouffe-Suzuki | 0.200 |
| 32 | Santana-Vargas-Mauer-Arcia-Dozier-Hunter-Suzuki-Hicks-Plouffe | 0.209 |
| 33 | Santana-Mauer-Vargas-Hunter-Arcia-Plouffe-Dozier-Suzuki-Hicks | 0.211 |
| 34 | Hicks-Santana-Hunter-Mauer-Arcia-Vargas-Dozier-Suzuki-Plouffe | 0.222 |
| 35 | Santana-Vargas-Mauer-Arcia-Hicks-Plouffe-Hunter-Dozier-Suzuki | 0.226 |
| 36 | Dozier-Santana-Vargas-Mauer-Arcia-Plouffe-Suzuki-Hunter-Hicks | 0.229 |
| 37 | Santana-Vargas-Hunter-Mauer-Arcia-Hicks-Plouffe-Dozier-Suzuki | 0.230 |
| 38 | Arcia-Santana-Vargas-Mauer-Dozier-Hunter-Hicks-Suzuki-Plouffe | 0.231 |
| 39 | Santana-Hunter-Mauer-Arcia-Vargas-Hicks-Plouffe-Dozier-Suzuki | 0.236 |
| 40 | Santana-Mauer-Vargas-Dozier-Arcia-Hunter-Plouffe-Suzuki-Hicks | 0.242 |
| 41 | Santana-Hunter-Mauer-Arcia-Dozier-Vargas-Hicks-Plouffe-Suzuki | 0.242 |
| 42 | Santana-Suzuki-Mauer-Arcia-Plouffe-Vargas-Hunter-Dozier-Hicks | 0.247 |
| 43 | Santana-Hunter-Arcia-Mauer-Vargas-Plouffe-Dozier-Hicks-Suzuki | 0.254 |
| 44 | Santana-Dozier-Vargas-Mauer-Arcia-Hunter-Plouffe-Hicks-Suzuki | 0.263 |
| 45 | Hunter-Dozier-Mauer-Arcia-Vargas-Santana-Suzuki-Plouffe-Hicks | 0.272 |
| 46 | Dozier-Mauer-Arcia-Vargas-Santana-Hunter-Suzuki-Plouffe-Hicks | 0.277 |
| 47 | Santana-Suzuki-Mauer-Vargas-Hicks-Arcia-Plouffe-Dozier-Hunter | 0.282 |
| 48 | Dozier-Hicks-Mauer-Vargas-Arcia-Santana-Hunter-Suzuki-Plouffe | 0.290 |
| 49 | Hicks-Dozier-Vargas-Mauer-Arcia-Santana-Hunter-Plouffe-Suzuki | 0.299 |
| 50 | Santana-Hunter-Mauer-Arcia-Dozier-Vargas-Suzuki-Hicks-Plouffe | 0.345 |
| .. | .. | .. |
| MLB | Santana-Dozier-Mauer-Vargas-Hunter-Plouffe-Arcia-Suzuki-Hicks | 0.587 |
| BAD | Suzuki-Plouffe-Hicks-Dozier-Santana-Arcia-Vargas-Hunter-Mauer | 1.714 |
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Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Santana | 32 | 12 | 0 | 0 | 1 | 5 | 0 | 0 | 0 |
| Mauer | 0 | 18 | 20 | 12 | 0 | 0 | 0 | 0 | 0 |
| Arcia | 1 | 0 | 9 | 23 | 16 | 1 | 0 | 0 | 0 |
| Vargas | 0 | 6 | 19 | 13 | 8 | 4 | 0 | 0 | 0 |
| Hunter | 5 | 7 | 2 | 1 | 5 | 9 | 10 | 2 | 9 |
| Plouffe | 0 | 0 | 0 | 0 | 4 | 13 | 14 | 12 | 7 |
| Hicks | 4 | 1 | 0 | 0 | 7 | 7 | 9 | 9 | 13 |
| Suzuki | 0 | 3 | 0 | 0 | 0 | 4 | 12 | 17 | 14 |
| Dozier | 8 | 3 | 0 | 1 | 9 | 7 | 5 | 10 | 7 |
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Synergy
20 Most Common Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 33 | Mauer | Arcia |
| 2 | 22 | Santana | Mauer |
| 3 | 16 | Mauer | Vargas |
| 4 | 16 | Arcia | Vargas |
| 5 | 15 | Dozier | Suzuki |
| 6 | 14 | Vargas | Mauer |
| 7 | 14 | Plouffe | Dozier |
| 8 | 14 | Suzuki | Hicks |
| 9 | 13 | Plouffe | Hicks |
| 10 | 13 | Hicks | Suzuki |
| 11 | 12 | Vargas | Arcia |
| 12 | 12 | Suzuki | Plouffe |
| 13 | 11 | Santana | Hunter |
| 14 | 11 | Hunter | Santana |
| 15 | 11 | Hunter | Plouffe |
| 16 | 11 | Plouffe | Suzuki |
| 17 | 11 | Hicks | Santana |
| 18 | 11 | Dozier | Santana |
| 19 | 10 | Santana | Vargas |
| 20 | 10 | Arcia | Plouffe |
| 20 | 10 | Suzuki | Santana |
20 Most Common Back to Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 16 | Mauer | Arcia | Vargas |
| 2 | 13 | Vargas | Mauer | Arcia |
| 3 | 12 | Mauer | Vargas | Arcia |
| 4 | 11 | Santana | Mauer | Arcia |
| 5 | 11 | Santana | Mauer | Vargas |
| 6 | 9 | Santana | Vargas | Mauer |
| 7 | 8 | Hunter | Santana | Mauer |
| 8 | 8 | Dozier | Santana | Mauer |
| 9 | 7 | Plouffe | Dozier | Suzuki |
| 10 | 6 | Mauer | Arcia | Dozier |
| 11 | 6 | Plouffe | Hicks | Suzuki |
| 12 | 6 | Plouffe | Suzuki | Hicks |
| 13 | 6 | Suzuki | Hicks | Santana |
| 14 | 5 | Mauer | Arcia | Plouffe |
| 15 | 5 | Hunter | Mauer | Arcia |
| 16 | 5 | Suzuki | Plouffe | Hicks |
| 17 | 5 | Suzuki | Dozier | Santana |
| 18 | 5 | Dozier | Suzuki | Hicks |
| 19 | 4 | Santana | Hunter | Mauer |
| 20 | 4 | Arcia | Vargas | Hunter |
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Tuesday, February 10, 2015
Toronto Blue Jays - 2015 Most Optimal Lineups
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Toronto Blue Jays. I started out with over 100,000 permutations of lineups and I slowly widdled it down to the top 50 lineups. For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup.bbThe simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. Sure, the Blue Jays manager won't use many of these lineups because they might not be prototypical but that is not part of the exercise. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 50 Lineups
Batting Order Frequency Table
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Synergy
20 Most Common Back to Back Occurrences
20 Most Common Back to Back to Back Occurrences
Reyes: Switch hitter with good speed and doesn't strike-out a lot. Has a nearly identical lineup profile as Saunders does.
Encarnacion: Good power and draws a nice amount of walks. The simulator likes him hitting either third or fourth but also makes an appearance at each lineup spot 1 thru 7.
Bautista: Great power and draws a lot of walks. Here is your cleanup hitter. If not cleanup can also fit in as the #3 hitter.
Donaldson: Like many of the players to follow, the simulator shows Donaldson with a lot of lineup position diversity. His best spot is fifth but also shines at 6th and 7th. Donaldson hits for good power but doesn't hit RHP real well (compared to LHP).
Pompey: Good speed and will clear the bases with an occasional triple. The simulator likes him hitting 6th the most but can find a good lineup to fit in at any of the non traditional power spots (3-4-5).
Izturis: Doesn't do anything real well on the offensive side but the simulator find him doing the least amount of damage batting either ninth or seventh and surprisingly finds his way to the third spot in seven of the top fifty lineups.
Navarro: Definitely the turtle of the team, the simulator likes him batting 8th though it can live with him in the sixth thru ninth spots. While a switch hitter, Navarro does much better historically against LHP.
Martin: Makes three appearances in seven different lineup spots on the top fifty lineup chart. Though the simulator does like Martin hitting 9th, almost as a second leadoff hitter.
............................................................................................................................
I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 Toronto Blue Jays. I started out with over 100,000 permutations of lineups and I slowly widdled it down to the top 50 lineups. For the starting nine players, I used the projected starting lineup from MLB Depth Charts The top 50 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors, such as rookies not being allowed to hit near the top of the lineup.bbThe simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. Sure, the Blue Jays manager won't use many of these lineups because they might not be prototypical but that is not part of the exercise. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 50 Lineups
| Rank | Lineup | Wins/162 Behind |
|---|---|---|
| 1 | Saunders-Pompey-Encarnacion-Bautista-Reyes-Izturis-Donaldson-Navarro-Martin | 0.000 |
| 2 | Izturis-Reyes-Encarnacion-Bautista-Saunders-Martin-Donaldson-Pompey-Navarro | 0.030 |
| 3 | Reyes-Saunders-Bautista-Encarnacion-Martin-Donaldson-Navarro-Pompey-Izturis | 0.038 |
| 4 | Saunders-Reyes-Bautista-Encarnacion-Donaldson-Pompey-Navarro-Izturis-Martin | 0.058 |
| 5 | Reyes-Saunders-Encarnacion-Bautista-Donaldson-Pompey-Izturis-Navarro-Martin | 0.070 |
| 6 | Reyes-Saunders-Bautista-Encarnacion-Donaldson-Pompey-Izturis-Navarro-Martin | 0.077 |
| 7 | Saunders-Pompey-Encarnacion-Bautista-Reyes-Izturis-Donaldson-Martin-Navarro | 0.079 |
| 8 | Saunders-Reyes-Izturis-Bautista-Encarnacion-Donaldson-Navarro-Martin-Pompey | 0.106 |
| 9 | Martin-Reyes-Encarnacion-Bautista-Saunders-Donaldson-Navarro-Pompey-Izturis | 0.125 |
| 10 | Bautista-Reyes-Encarnacion-Donaldson-Saunders-Pompey-Izturis-Navarro-Martin | 0.148 |
| 11 | Saunders-Donaldson-Encarnacion-Bautista-Reyes-Izturis-Pompey-Navarro-Martin | 0.158 |
| 12 | Saunders-Reyes-Encarnacion-Bautista-Izturis-Pompey-Navarro-Donaldson-Martin | 0.175 |
| 13 | Saunders-Reyes-Bautista-Encarnacion-Donaldson-Navarro-Martin-Izturis-Pompey | 0.181 |
| 14 | Saunders-Reyes-Izturis-Encarnacion-Bautista-Pompey-Navarro-Donaldson-Martin | 0.186 |
| 15 | Reyes-Saunders-Donaldson-Encarnacion-Bautista-Pompey-Navarro-Martin-Izturis | 0.197 |
| 16 | Pompey-Reyes-Izturis-Bautista-Encarnacion-Saunders-Donaldson-Navarro-Martin | 0.199 |
| 17 | Reyes-Encarnacion-Martin-Bautista-Saunders-Navarro-Donaldson-Pompey-Izturis | 0.201 |
| 18 | Izturis-Reyes-Encarnacion-Bautista-Donaldson-Saunders-Martin-Pompey-Navarro | 0.212 |
| 19 | Reyes-Izturis-Encarnacion-Bautista-Saunders-Navarro-Martin-Donaldson-Pompey | 0.214 |
| 20 | Saunders-Izturis-Martin-Bautista-Reyes-Encarnacion-Donaldson-Pompey-Navarro | 0.222 |
| 21 | Saunders-Reyes-Encarnacion-Bautista-Donaldson-Navarro-Martin-Izturis-Pompey | 0.226 |
| 22 | Reyes-Saunders-Bautista-Encarnacion-Donaldson-Pompey-Martin-Izturis-Navarro | 0.228 |
| 23 | Saunders-Reyes-Bautista-Encarnacion-Donaldson-Pompey-Izturis-Martin-Navarro | 0.239 |
| 24 | Reyes-Saunders-Encarnacion-Bautista-Martin-Donaldson-Izturis-Pompey-Navarro | 0.240 |
| 25 | Reyes-Saunders-Bautista-Encarnacion-Donaldson-Navarro-Pompey-Izturis-Martin | 0.240 |
| 26 | Reyes-Encarnacion-Martin-Bautista-Donaldson-Pompey-Navarro-Saunders-Izturis | 0.249 |
| 27 | Saunders-Pompey-Bautista-Encarnacion-Reyes-Izturis-Navarro-Donaldson-Martin | 0.254 |
| 28 | Reyes-Saunders-Martin-Encarnacion-Bautista-Navarro-Donaldson-Pompey-Izturis | 0.265 |
| 29 | Saunders-Reyes-Martin-Encarnacion-Bautista-Pompey-Donaldson-Izturis-Navarro | 0.275 |
| 30 | Pompey-Reyes-Bautista-Encarnacion-Donaldson-Martin-Saunders-Navarro-Izturis | 0.281 |
| 31 | Saunders-Martin-Encarnacion-Bautista-Reyes-Donaldson-Izturis-Navarro-Pompey | 0.291 |
| 32 | Donaldson-Pompey-Bautista-Saunders-Reyes-Izturis-Encarnacion-Navarro-Martin | 0.293 |
| 33 | Reyes-Saunders-Encarnacion-Donaldson-Bautista-Pompey-Izturis-Navarro-Martin | 0.296 |
| 34 | Saunders-Reyes-Izturis-Encarnacion-Donaldson-Martin-Bautista-Pompey-Navarro | 0.300 |
| 35 | Saunders-Pompey-Bautista-Encarnacion-Martin-Donaldson-Reyes-Navarro-Izturis | 0.301 |
| 36 | Bautista-Saunders-Encarnacion-Donaldson-Reyes-Martin-Pompey-Navarro-Izturis | 0.309 |
| 37 | Reyes-Saunders-Bautista-Donaldson-Encarnacion-Pompey-Izturis-Navarro-Martin | 0.310 |
| 38 | Donaldson-Reyes-Bautista-Encarnacion-Saunders-Pompey-Navarro-Martin-Izturis | 0.313 |
| 39 | Encarnacion-Donaldson-Martin-Bautista-Reyes-Saunders-Izturis-Navarro-Pompey | 0.333 |
| 40 | Pompey-Martin-Encarnacion-Bautista-Saunders-Reyes-Izturis-Donaldson-Navarro | 0.338 |
| 41 | Bautista-Saunders-Martin-Encarnacion-Reyes-Donaldson-Pompey-Navarro-Izturis | 0.338 |
| 42 | Izturis-Saunders-Encarnacion-Bautista-Reyes-Pompey-Donaldson-Navarro-Martin | 0.340 |
| 43 | Reyes-Martin-Encarnacion-Bautista-Donaldson-Pompey-Saunders-Navarro-Izturis | 0.352 |
| 44 | Encarnacion-Reyes-Bautista-Donaldson-Saunders-Pompey-Navarro-Martin-Izturis | 0.362 |
| 45 | Reyes-Navarro-Encarnacion-Bautista-Saunders-Donaldson-Izturis-Pompey-Martin | 0.362 |
| 46 | Encarnacion-Saunders-Donaldson-Bautista-Reyes-Martin-Izturis-Navarro-Pompey | 0.363 |
| 47 | Donaldson-Saunders-Izturis-Bautista-Reyes-Pompey-Encarnacion-Navarro-Martin | 0.367 |
| 48 | Donaldson-Saunders-Izturis-Bautista-Reyes-Encarnacion-Pompey-Navarro-Martin | 0.394 |
| 49 | Reyes-Donaldson-Martin-Bautista-Saunders-Encarnacion-Pompey-Navarro-Izturis | 0.417 |
| 50 | Bautista-Reyes-Izturis-Encarnacion-Donaldson-Saunders-Martin-Navarro-Pompey | 0.442 |
| .. | ||
| BAD | Navarro-Izturis-Reyes-Saunders-Pompey-Martin-Donaldson-Encarnacion-Bautista | 2.125 |
Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Saunders | 16 | 16 | 0 | 1 | 10 | 4 | 2 | 1 | 0 |
| Reyes | 16 | 18 | 0 | 0 | 14 | 1 | 1 | 0 | 0 |
| Encarnacion | 3 | 2 | 19 | 18 | 3 | 3 | 2 | 0 | 0 |
| Bautista | 4 | 0 | 14 | 26 | 5 | 0 | 1 | 0 | 0 |
| Donaldson | 4 | 3 | 2 | 5 | 14 | 8 | 9 | 5 | 0 |
| Pompey | 3 | 5 | 0 | 0 | 0 | 18 | 6 | 10 | 8 |
| Izturis | 3 | 2 | 7 | 0 | 1 | 5 | 12 | 6 | 14 |
| Navarro | 0 | 1 | 0 | 0 | 0 | 6 | 11 | 22 | 10 |
| Martin | 1 | 3 | 8 | 0 | 3 | 5 | 6 | 6 | 18 |
.
Synergy
20 Most Common Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 20 | Encarnacion | Bautista |
| 2 | 19 | Navarro | Martin |
| 3 | 17 | Pompey | Navarro |
| 4 | 15 | Encarnacion | Donaldson |
| 5 | 14 | Donaldson | Pompey |
| 6 | 13 | Bautista | Encarnacion |
| 7 | 12 | Reyes | Izturis |
| 8 | 12 | Bautista | Reyes |
| 9 | 11 | Saunders | Reyes |
| 10 | 11 | Reyes | Saunders |
| 11 | 11 | Pompey | Izturis |
| 12 | 11 | Izturis | Navarro |
| 13 | 10 | Reyes | Encarnacion |
| 14 | 10 | Bautista | Saunders |
| 15 | 10 | Donaldson | Navarro |
| 16 | 9 | Izturis | Reyes |
| 17 | 9 | Navarro | Izturis |
| 18 | 8 | Donaldson | Martin |
| 19 | 8 | Navarro | Pompey |
| 20 | 8 | Martin | Donaldson |
| 20 | 8 | Martin | Izturis |
20 Most Common Back to Back to Back Occurrences
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 8 | Bautista | Encarnacion | Donaldson |
| 2 | 6 | Donaldson | Navarro | Martin |
| 3 | 6 | Pompey | Navarro | Izturis |
| 4 | 6 | Navarro | Martin | Izturis |
| 5 | 5 | Saunders | Reyes | Izturis |
| 6 | 5 | Reyes | Saunders | Bautista |
| 7 | 5 | Reyes | Encarnacion | Bautista |
| 8 | 5 | Reyes | Bautista | Encarnacion |
| 9 | 5 | Reyes | Izturis | Encarnacion |
| 10 | 5 | Encarnacion | Bautista | Saunders |
| 11 | 5 | Encarnacion | Bautista | Reyes |
| 12 | 5 | Encarnacion | Donaldson | Pompey |
| 13 | 5 | Donaldson | Pompey | Izturis |
| 14 | 5 | Donaldson | Pompey | Navarro |
| 15 | 5 | Pompey | Izturis | Navarro |
| 16 | 5 | Pompey | Navarro | Martin |
| 17 | 5 | Izturis | Navarro | Martin |
| 18 | 5 | Martin | Reyes | Saunders |
| 19 | 5 | Martin | Encarnacion | Bautista |
| 20 | 4 | Saunders | Bautista | Encarnacion |
Analysis
Saunders: Hits left-handed and does well against RHP. Has decent speed and power and the simulator likes him hitting either first or second and can live with him hitting fifth as well.Reyes: Switch hitter with good speed and doesn't strike-out a lot. Has a nearly identical lineup profile as Saunders does.
Encarnacion: Good power and draws a nice amount of walks. The simulator likes him hitting either third or fourth but also makes an appearance at each lineup spot 1 thru 7.
Bautista: Great power and draws a lot of walks. Here is your cleanup hitter. If not cleanup can also fit in as the #3 hitter.
Donaldson: Like many of the players to follow, the simulator shows Donaldson with a lot of lineup position diversity. His best spot is fifth but also shines at 6th and 7th. Donaldson hits for good power but doesn't hit RHP real well (compared to LHP).
Pompey: Good speed and will clear the bases with an occasional triple. The simulator likes him hitting 6th the most but can find a good lineup to fit in at any of the non traditional power spots (3-4-5).
Izturis: Doesn't do anything real well on the offensive side but the simulator find him doing the least amount of damage batting either ninth or seventh and surprisingly finds his way to the third spot in seven of the top fifty lineups.
Navarro: Definitely the turtle of the team, the simulator likes him batting 8th though it can live with him in the sixth thru ninth spots. While a switch hitter, Navarro does much better historically against LHP.
Martin: Makes three appearances in seven different lineup spots on the top fifty lineup chart. Though the simulator does like Martin hitting 9th, almost as a second leadoff hitter.
............................................................................................................................
Tuesday, February 03, 2015
San Francisco Giants - 2015 Most Optimal Lineup
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 San Francisco Giants. I started out with over 2,000 permutations of lineups, a group that was filtered to remove such things as left handed hitters hitting back to back or the pitcher not hitting 8th or 9th etc... and I slowly widdled it down to the top 25 lineups. I also compared the best lineup against the lineup that MLB Depth Charts (0.40 wins/162 games worse) shows as a likely lineup and also one of the worst lineups to see what kind of spread there is. The top 25 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors. It is not like Joe Panik's mom is going to be calling up Giants management in tears asking for Joe not to bat 4th because he is going to have to change his approach at the plate. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. Sure, the Giants manager won't use many of these lineups because they might not be prototypical but that is not part of the exercise. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 25 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 25 Optimal Lineups
Batting Order Frequency Table
Synergy
20 Most Common Back to Back Occurrences in Lineup:
10 Most Common Back to Back to Back Occurrences in Lineup:
Aoki: Like Pagan, the simulator pegs Aoki at one of the first two spots in the lineup with the occasional drop to fifth. There are even two appearances in the top 50 lineups with Aoki batting 9th.
Posey: The Giants will get the most bang for their buck with Posey hitting third or fourth which is really the only two spots the Giants would ever hit him in.
Belt: Shows up in many different lineup spots with second thru sixth being the best spots for him. Belt finds himself paired either in front of or immediately after Pence in the lineup in 33 of the top 50 lineups. The threesome of Posey-Belt-Pence show up as the second most likely consecutive trio in the top lineups.
Pence: Finds himself all over the radar on the first six lineup spots with fifth and sixth being his best spots. Which is pretty much in line where Pence expects to bat in the 2015 lineup.
Panik: Appears all over the place in the top 50 lineups. The only two spots he doesn't appear in is leadoff and eighth. Panik makes more than a few surprise appearances in the middle of the lineup in the top list which may come as a surprise. The Giants won't likely bat him in the middle of the lineup but the simulator does not take into account psychological reasons (like experience) for not batting a player in a certain spot. With the L-R-L requirement Panik ends up all over the place.
McGeHee: Looks to be a solid fit at the seventh and eighth spots as a late source of power in the lineup before the black hole of the pitcher bats. McGeHee-Pitcher is the number one most common consecutive batting duo in the lineup and McGeHee-Pitcher-Crawford is the number one most common threesome.
Crawford: He shows up all over the place but is a best fit hitting seventh, eighth, ninth or leadoff.
Pitcher: The pitcher shows up hitting eighth in 42% of the top lineups. Most MLB managers will not hit the pitcher eighth for psychological reasons but if done correctly with the right personnel and lineup construction it is a good thing.
I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 San Francisco Giants. I started out with over 2,000 permutations of lineups, a group that was filtered to remove such things as left handed hitters hitting back to back or the pitcher not hitting 8th or 9th etc... and I slowly widdled it down to the top 25 lineups. I also compared the best lineup against the lineup that MLB Depth Charts (0.40 wins/162 games worse) shows as a likely lineup and also one of the worst lineups to see what kind of spread there is. The top 25 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. You will see a few lineups that may seem strange in a most optimal list but keep in mind the simulator does not take into account psychological factors. It is not like Joe Panik's mom is going to be calling up Giants management in tears asking for Joe not to bat 4th because he is going to have to change his approach at the plate. The simulator just takes the Steamer projection inputs along with a speed rating for base running and gives you the best lineups. Sure, the Giants manager won't use many of these lineups because they might not be prototypical but that is not part of the exercise. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 25 lineups and a batting order spot frequency table, where you can see how many times each player appeared in each of the top 50 lineups.
Top 25 Optimal Lineups
| Rank | Lineup | Wins behind/162 games |
|---|---|---|
| 1 | Pagan-Aoki-Posey-Panik-Pence-Belt-McGeHee-Pitcher-Crawford | 0.000 |
| 2 | Pagan-Aoki-Posey-Belt-Pence-Panik-McGeHee-Pitcher-Crawford | 0.027 |
| 3 | Pagan-Aoki-Posey-Belt-Pence-Crawford-McGeHee-Pitcher-Panik | 0.060 |
| 4 | Aoki-Pagan-Panik-Posey-Belt-Pence-Crawford-McGeHee-Pitcher | 0.116 |
| 5 | Crawford-Pagan-Belt-Posey-Aoki-Pence-Panik-McGeHee-Pitcher | 0.239 |
| 6 | Pence-Aoki-Posey-Belt-Pagan-Panik-McGeHee-Pitcher-Crawford | 0.247 |
| 7 | Aoki-Pagan-Belt-Posey-Panik-Pence-Crawford-McGeHee-Pitcher | 0.258 |
| 8 | Aoki-Pagan-Belt-Posey-Crawford-Pence-Panik-McGeHee-Pitcher | 0.263 |
| 9 | Belt-Pagan-Panik-Posey-Aoki-Pence-Crawford-McGeHee-Pitcher | 0.277 |
| 10 | Pence-Aoki-Posey-Panik-Pagan-Belt-McGeHee-Pitcher-Crawford | 0.286 |
| 11 | Pagan-Aoki-Posey-Panik-Pence-Crawford-McGeHee-Pitcher-Belt | 0.294 |
| 12 | Aoki-Pagan-Panik-Posey-Crawford-Pence-Belt-McGeHee-Pitcher | 0.296 |
| 13 | Crawford-Pagan-Panik-Posey-Aoki-Pence-Belt-McGeHee-Pitcher | 0.301 |
| 14 | Aoki-Pence-Panik-Posey-Belt-Pagan-Crawford-McGeHee-Pitcher | 0.321 |
| 15 | Pagan-Aoki-Posey-Crawford-Pence-Belt-McGeHee-Pitcher-Panik | 0.325 |
| 16 | Pagan-Aoki-Pence-Panik-Posey-Belt-McGeHee-Pitcher-Crawford | 0.327 |
| 17 | Pagan-Panik-Posey-Belt-Pence-Aoki-McGeHee-Pitcher-Crawford | 0.357 |
| 18 | Belt-Pence-Crawford-Posey-Aoki-Pagan-Panik-McGeHee-Pitcher | 0.360 |
| 19 | Aoki-Pagan-Panik-Pence-Belt-Posey-Crawford-McGeHee-Pitcher | 0.361 |
| 20 | Crawford-Pagan-Panik-Pence-Aoki-Posey-Belt-McGeHee-Pitcher | 0.393 |
| 21 | Pagan-Aoki-Posey-Belt-Pence-Panik-McGeHee-Crawford-Pitcher | 0.400 |
| 22 | Pence-Aoki-Posey-Belt-Pagan-Crawford-McGeHee-Pitcher-Panik | 0.407 |
| 23 | Pagan-Panik-Posey-Belt-Pence-Crawford-McGeHee-Pitcher-Aoki | 0.428 |
| 24 | Crawford-Pence-Panik-Posey-Aoki-Pagan-Belt-McGeHee-Pitcher | 0.442 |
| 25 | Pagan-Aoki-Posey-Belt-Pence-Panik-McGeHee-Crawford-Pitcher | 0.442 |
| .. | ||
| Bad | McGeHee-Belt-Pagan-Aoki-Pence-Panik-Crawford-Posey-Pitcher | 2.438 |
Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Pagan | 19 | 17 | 0 | 0 | 5 | 9 | 0 | 0 | 0 |
| Aoki | 17 | 17 | 0 | 1 | 9 | 3 | 1 | 0 | 2 |
| Posey | 0 | 3 | 24 | 17 | 2 | 4 | 0 | 0 | 0 |
| Belt | 3 | 1 | 8 | 14 | 10 | 8 | 4 | 0 | 2 |
| Pence | 4 | 7 | 2 | 8 | 18 | 11 | 0 | 0 | 0 |
| Panik | 0 | 5 | 14 | 7 | 2 | 8 | 8 | 0 | 6 |
| McGeHee | 0 | 0 | 0 | 1 | 0 | 3 | 24 | 21 | 1 |
| Crawford | 7 | 0 | 2 | 2 | 4 | 4 | 13 | 8 | 10 |
| Pitcher | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 21 | 29 |
Synergy
20 Most Common Back to Back Occurrences in Lineup:
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 37 | McGeHee | Pitcher |
| 2 | 22 | Pagan | Panik |
| 3 | 22 | Posey | Belt |
| 4 | 19 | Aoki | Posey |
| 5 | 18 | Pitcher | Aoki |
| 6 | 17 | Aoki | Pagan |
| 7 | 17 | Belt | Pence |
| 8 | 17 | Pitcher | Crawford |
| 9 | 16 | Pence | Belt |
| 10 | 16 | Panik | McGeHee |
| 11 | 15 | Pagan | Aoki |
| 12 | 15 | Panik | Posey |
| 13 | 13 | Belt | McGeHee |
| 14 | 13 | Crawford | Pagan |
| 15 | 13 | Crawford | Pitcher |
| 16 | 12 | Pence | Panik |
| 17 | 12 | Panik | Pence |
| 18 | 12 | Crawford | McGeHee |
| 19 | 11 | McGeHee | Crawford |
| 20 | 10 | Aoki | Pence |
| 20 | 10 | Posey | Panik |
| 20 | 10 | Belt | Pagan |
| 20 | 10 | Belt | Posey |
10 Most Common Back to Back to Back Occurrences in Lineup:
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 17 | McGeHee | Pitcher | Crawford |
| 2 | 15 | Posey | Belt | Pence |
| 3 | 12 | Pagan | Aoki | Posey |
| 4 | 12 | Panik | McGeHee | Pitcher |
| 5 | 12 | McGeHee | Pitcher | Aoki |
| 6 | 12 | Crawford | McGeHee | Pitcher |
| 7 | 12 | Pitcher | Aoki | Pagan |
| 8 | 11 | Pagan | Panik | Posey |
| 9 | 11 | Aoki | Pagan | Panik |
| 10 | 11 | McGeHee | Crawford | Pitcher |
| 10 | 11 | Pitcher | Crawford | Pagan |
Analysis
Pagan: The simulator likes the switch hitting Pagan batting first or second in the lineup. There are a couple of permutations where the simulator likes Pagan batting sixth but he seems best suited for the top of the lineup which is where he is likely to bat in reality.Aoki: Like Pagan, the simulator pegs Aoki at one of the first two spots in the lineup with the occasional drop to fifth. There are even two appearances in the top 50 lineups with Aoki batting 9th.
Posey: The Giants will get the most bang for their buck with Posey hitting third or fourth which is really the only two spots the Giants would ever hit him in.
Belt: Shows up in many different lineup spots with second thru sixth being the best spots for him. Belt finds himself paired either in front of or immediately after Pence in the lineup in 33 of the top 50 lineups. The threesome of Posey-Belt-Pence show up as the second most likely consecutive trio in the top lineups.
Pence: Finds himself all over the radar on the first six lineup spots with fifth and sixth being his best spots. Which is pretty much in line where Pence expects to bat in the 2015 lineup.
Panik: Appears all over the place in the top 50 lineups. The only two spots he doesn't appear in is leadoff and eighth. Panik makes more than a few surprise appearances in the middle of the lineup in the top list which may come as a surprise. The Giants won't likely bat him in the middle of the lineup but the simulator does not take into account psychological reasons (like experience) for not batting a player in a certain spot. With the L-R-L requirement Panik ends up all over the place.
McGeHee: Looks to be a solid fit at the seventh and eighth spots as a late source of power in the lineup before the black hole of the pitcher bats. McGeHee-Pitcher is the number one most common consecutive batting duo in the lineup and McGeHee-Pitcher-Crawford is the number one most common threesome.
Crawford: He shows up all over the place but is a best fit hitting seventh, eighth, ninth or leadoff.
Pitcher: The pitcher shows up hitting eighth in 42% of the top lineups. Most MLB managers will not hit the pitcher eighth for psychological reasons but if done correctly with the right personnel and lineup construction it is a good thing.
Friday, January 30, 2015
St Louis Cardinals - Most Optimal 2015 Lineups
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I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 St Louis Cardinals. I started out with over 10,000 permutations of lineups, a group that was filtered to remove such things as too many left handed hitters hitting back to back or the pitcher not hitting 8th or 9th etc... and I slowly widdled it down to the top 50 lineups. I also compared the best lineup against the lineup that MLB Depth Charts shows as a likely lineup and also one of the worst lineups to see what kind of spread there is. The top 50 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequence table, where you can see how many times each player appeared in each of the top 50 lineup.
Top 50 Most Optimal Lineups
.
.
Batting Order Frequence Table
Synergy:
10 most common back to back occurrences in lineup.
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10 most common back to back to back occurrences in lineup.
.
.
Carpenter: Surpsingly does well at cleanup along with Adams but also does well among the 1-2-5 spots like Heyward. Carpenter shows a lot of lineup versatility if there is such a thing.
Holliday: Should hit third.
Adams: The teams best cleanup hitter but can also move down to fifth in the lineup if need be.
Wong: No one great spot for Wong but he probably shows the most "lineup versatility" as anyone on the team There are 6 lineup slots where Wong appeared at least 6 times. When it comes to batting order spots, Wong is definitely the Nomad of the team. Wong even makes 9 appearances hitting 9th, one spot behind the pitcher.
Peralta: The simulator likes Peralta hitting 6th as he provides some pretty decent back of the lineup power. He should definitely stay out of the top five spots in the lineup.
Molina: 6-7-8 are the best spots for Molina as only Heyward and Molina have a 14 or higher on their third most frequented lineup spot.
Jay: Looks like the simulator likes Jay setting the table whether it be as the leadoff hitter or the quasi-leadoff hitter batting 9th.
Pitcher: With Jay and Wong making appearances in the 9th spot the simulator pretty much calls it a crapshoot at hitting the pitcher 8th or 9th. The pitcher should bat immediately after Molina does.
I am using my simulator that plays actual baseball games to find what it believes are the most optimal lineups for the 2015 St Louis Cardinals. I started out with over 10,000 permutations of lineups, a group that was filtered to remove such things as too many left handed hitters hitting back to back or the pitcher not hitting 8th or 9th etc... and I slowly widdled it down to the top 50 lineups. I also compared the best lineup against the lineup that MLB Depth Charts shows as a likely lineup and also one of the worst lineups to see what kind of spread there is. The top 50 lineups all came within a half of a win per 162 games so really anything in that range is pretty good. When you start nearing a full win differential with the top lineup then you definitely have problems. I typically simulated each lineup over 1 million times which eliminated a large portion of the random noise and I did so only against a right handed pitcher. Below are a list of the top 50 lineups and a batting order spot frequence table, where you can see how many times each player appeared in each of the top 50 lineup.
Top 50 Most Optimal Lineups
| Rank | Lineup | Wins/162 Behind |
|---|---|---|
| 1 | Heyward-Carpenter-Holliday-Adams-Wong-Molina-Peralta-Pitcher-Jay | 0 |
| 2 | Carpenter-Heyward-Holliday-Adams-Wong-Molina-Peralta-Pitcher-Jay | 0.014 |
| 3 | Wong-Jay-Holliday-Carpenter-Heyward-Peralta-Adams-Molina-Pitcher | 0.015 |
| 4 | Carpenter-Heyward-Holliday-Adams-Wong-Peralta-Molina-Pitcher-Jay | 0.032 |
| 5 | Heyward-Jay-Holliday-Carpenter-Adams-Peralta-Molina-Pitcher-Wong | 0.066 |
| 6 | Wong-Heyward-Holliday-Carpenter-Adams-Peralta-Molina-Pitcher-Jay | 0.086 |
| 7 | Heyward-Jay-Holliday-Carpenter-Adams-Molina-Peralta-Pitcher-Wong | 0.102 |
| 8 | Heyward-Jay-Holliday-Carpenter-Adams-Peralta-Wong-Molina-Pitcher | 0.120 |
| 9 | Jay-Heyward-Holliday-Carpenter-Adams-Peralta-Molina-Pitcher-Wong | 0.131 |
| 10 | Wong-Jay-Holliday-Carpenter-Heyward-Molina-Adams-Peralta-Pitcher | 0.151 |
| 11 | Jay-Heyward-Holliday-Carpenter-Adams-Peralta-Wong-Molina-Pitcher | 0.167 |
| 12 | Jay-Heyward-Holliday-Carpenter-Wong-Peralta-Adams-Molina-Pitcher | 0.171 |
| 13 | Jay-Heyward-Holliday-Carpenter-Adams-Molina-Peralta-Pitcher-Wong | 0.175 |
| 14 | Heyward-Carpenter-Holliday-Adams-Wong-Peralta-Jay-Molina-Pitcher | 0.184 |
| 15 | Carpenter-Jay-Holliday-Adams-Heyward-Peralta-Wong-Molina-Pitcher | 0.199 |
| 16 | Jay-Heyward-Holliday-Adams-Carpenter-Peralta-Wong-Molina-Pitcher | 0.200 |
| 17 | Heyward-Jay-Holliday-Adams-Carpenter-Peralta-Wong-Molina-Pitcher | 0.209 |
| 18 | Wong-Jay-Peralta-Carpenter-Heyward-Holliday-Adams-Molina-Pitcher | 0.243 |
| 19 | Heyward-Adams-Holliday-Carpenter-Wong-Molina-Peralta-Pitcher-Jay | 0.247 |
| 20 | Carpenter-Heyward-Holliday-Adams-Jay-Peralta-Molina-Pitcher-Wong | 0.253 |
| 21 | Heyward-Wong-Holliday-Adams-Carpenter-Peralta-Molina-Pitcher-Jay | 0.257 |
| 22 | Jay-Wong-Holliday-Carpenter-Heyward-Molina-Adams-Peralta-Pitcher | 0.266 |
| 23 | Heyward-Adams-Holliday-Carpenter-Wong-Peralta-Molina-Pitcher-Jay | 0.269 |
| 24 | Heyward-Jay-Holliday-Carpenter-Adams-Molina-Wong-Peralta-Pitcher | 0.269 |
| 25 | Wong-Jay-Molina-Carpenter-Heyward-Holliday-Adams-Peralta-Pitcher | 0.284 |
| 26 | Jay-Carpenter-Holliday-Heyward-Adams-Peralta-Molina-Pitcher-Wong | 0.286 |
| 27 | Heyward-Carpenter-Holliday-Adams-Molina-Wong-Peralta-Pitcher-Jay | 0.286 |
| 28 | Jay-Carpenter-Holliday-Adams-Heyward-Peralta-Molina-Pitcher-Wong | 0.288 |
| 29 | Heyward-Holliday-Carpenter-Adams-Peralta-Wong-Molina-Pitcher-Jay | 0.289 |
| 30 | Carpenter-Heyward-Holliday-Adams-Wong-Molina-Jay-Peralta-Pitcher | 0.292 |
| 31 | Jay-Adams-Holliday-Carpenter-Heyward-Peralta-Wong-Molina-Pitcher | 0.299 |
| 32 | Heyward-Wong-Holliday-Carpenter-Adams-Peralta-Jay-Molina-Pitcher | 0.305 |
| 33 | Wong-Carpenter-Holliday-Adams-Heyward-Peralta-Molina-Pitcher-Jay | 0.310 |
| 34 | Carpenter-Jay-Holliday-Adams-Heyward-Peralta-Molina-Pitcher-Wong | 0.310 |
| 35 | Peralta-Heyward-Carpenter-Holliday-Adams-Wong-Molina-Pitcher-Jay | 0.317 |
| 36 | Jay-Carpenter-Holliday-Heyward-Adams-Peralta-Wong-Molina-Pitcher | 0.326 |
| 37 | Jay-Wong-Molina-Carpenter-Heyward-Holliday-Adams-Peralta-Pitcher | 0.327 |
| 38 | Carpenter-Heyward-Holliday-Adams-Jay-Peralta-Wong-Molina-Pitcher | 0.327 |
| 39 | Wong-Carpenter-Holliday-Adams-Heyward-Peralta-Jay-Molina-Pitcher | 0.343 |
| 40 | Jay-Carpenter-Holliday-Adams-Heyward-Molina-Wong-Peralta-Pitcher | 0.348 |
| 41 | Jay-Heyward-Holliday-Adams-Carpenter-Molina-Peralta-Pitcher-Wong | 0.353 |
| 42 | Wong-Adams-Holliday-Carpenter-Heyward-Peralta-Molina-Pitcher-Jay | 0.372 |
| 43 | Heyward-Holliday-Adams-Carpenter-Peralta-Wong-Molina-Pitcher-Jay | 0.382 |
| 44 | Carpenter-Heyward-Holliday-Adams-Wong-Peralta-Jay-Molina-Pitcher | 0.388 |
| 45 | Carpenter-Wong-Holliday-Adams-Heyward-Molina-Peralta-Pitcher-Jay | 0.403 |
| 46 | Peralta-Heyward-Adams-Holliday-Carpenter-Wong-Molina-Pitcher-Jay | 0.433 |
| 47 | Heyward-Carpenter-Holliday-Adams-Wong-Molina-Jay-Pitcher-Peralta | 0.439 |
| 48 | Heyward-Peralta-Carpenter-Adams-Holliday-Wong-Molina-Pitcher-Jay | 0.469 |
| 49 | Heyward-Wong-Holliday-Adams-Carpenter-Molina-Peralta-Pitcher-Jay | 0.477 |
| 50 | Carpenter-Heyward-Holliday-Adams-Molina-Wong-Peralta-Pitcher-Jay | 0.485 |
| .. | .. | .. |
| MLBDC | Carpenter-Heyward-Holliday-Adams-Molina-Peralta-Jay-Wong-Pitcher | 1.090 |
| BAD | Adams-Peralta-Jay-Wong-Molina-Carpenter-Holliday-Heyward-Pitcher | 3.661 |
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Batting Order Frequence Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Heyward | 17 | 16 | 0 | 2 | 15 | 0 | 0 | 0 | 0 |
| Carpenter | 10 | 10 | 3 | 21 | 6 | 0 | 0 | 0 | 0 |
| Holliday | 0 | 2 | 42 | 2 | 1 | 3 | 0 | 0 | 0 |
| Adams | 0 | 4 | 2 | 25 | 12 | 0 | 7 | 0 | 0 |
| Wong | 8 | 6 | 0 | 0 | 10 | 7 | 10 | 0 | 9 |
| Peralta | 2 | 1 | 1 | 0 | 2 | 26 | 10 | 7 | 1 |
| Molina | 0 | 0 | 2 | 0 | 2 | 14 | 17 | 15 | 0 |
| Jay | 13 | 11 | 0 | 0 | 2 | 0 | 6 | 0 | 18 |
| Pitcher | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 28 | 22 |
Synergy:
10 most common back to back occurrences in lineup.
| Rank | Occurrences | Player 1 | Player 2 |
|---|---|---|---|
| 1 | 32 | Molina | Pitcher |
| 2 | 28 | Holliday | Adams |
| 3 | 26 | Pitcher | Jay |
| 4 | 19 | Heyward | Holliday |
| 5 | 19 | Holliday | Carpenter |
| 6 | 19 | Wong | Molina |
| 7 | 17 | Peralta | Pitcher |
| 8 | 15 | Carpenter | Heyward |
| 9 | 15 | Jay | Heyward |
| 10 | 14 | Pitcher | Wong |
10 most common back to back to back occurrences in lineup.
| Rank | Occurrences | Player 1 | Player 2 | Player 3 |
|---|---|---|---|---|
| 1 | 16 | Molina | Pitcher | Jay |
| 2 | 13 | Heyward | Holliday | Adams |
| 3 | 13 | Wong | Molina | Pitcher |
| 4 | 12 | Peralta | Molina | Pitcher |
| 5 | 12 | Pitcher | Jay | Heyward |
| 6 | 10 | Carpenter | Heyward | Holliday |
| 7 | 10 | Holliday | Carpenter | Adams |
| 8 | 10 | Peralta | Wong | Molina |
| 9 | 10 | Peralta | Pitcher | Jay |
| 10t | 9 | Carpenter | Holliday | Adams |
| 10t | 9 | Molina | Pitcher | Wong |
| 10t | 9 | Pitcher | Wong | Jay |
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Analysis
Heyward: Slots well at the top of the lineup as either the leadoff or second hitter. With others better suited for the 3rd or 4th spot in the lineup, Heyward also slots in well as the 5th hitter but should not hit in the 6th thru 9th slots.Carpenter: Surpsingly does well at cleanup along with Adams but also does well among the 1-2-5 spots like Heyward. Carpenter shows a lot of lineup versatility if there is such a thing.
Holliday: Should hit third.
Adams: The teams best cleanup hitter but can also move down to fifth in the lineup if need be.
Wong: No one great spot for Wong but he probably shows the most "lineup versatility" as anyone on the team There are 6 lineup slots where Wong appeared at least 6 times. When it comes to batting order spots, Wong is definitely the Nomad of the team. Wong even makes 9 appearances hitting 9th, one spot behind the pitcher.
Peralta: The simulator likes Peralta hitting 6th as he provides some pretty decent back of the lineup power. He should definitely stay out of the top five spots in the lineup.
Molina: 6-7-8 are the best spots for Molina as only Heyward and Molina have a 14 or higher on their third most frequented lineup spot.
Jay: Looks like the simulator likes Jay setting the table whether it be as the leadoff hitter or the quasi-leadoff hitter batting 9th.
Pitcher: With Jay and Wong making appearances in the 9th spot the simulator pretty much calls it a crapshoot at hitting the pitcher 8th or 9th. The pitcher should bat immediately after Molina does.
Friday, January 16, 2015
How Optimal Was The Royals 2014 Lineup
My simulator is a good tool for looking at optimal batting orders. It can play tens of thousands and even millions (with a smaller set of games) of games while keeping the opponent static which can give you a good idea which lineups win more games. I am using the Royals most common lineup that they used in the 2014 season and seeing how optimal the simulator thought it was. After doing this for the Dodgers and Cardinals, I decided to move on to the Kansas City Royals. I put in some filters to cut down on the number of lineup permutations. I tried to mimic what the Royals manager tended to do in not hitting lefties back to back other than the 9th then leadoff hitter etc... Of course you can't expect any manager to be implementing the most optimal lineup but you also don't want him to be giving away fractions of wins each game that can add up over a 162 game season. So down below, I list the Top 10 lineups along with the most common 2014 lineup in a table sorted by Wins/162 games. I also list a table showing the frequency of where each player batted in each of the top 50 lineups. I love the batting order frequency tables as they show you which players have a few dedicated positions in the order they should be hitting in and which players are more versatile in giving you an optimal lineup. I used 2014 final season stats as the input projections for each hitter because that is for the most part similar to the data that the manager went by. And I did all the simulations with the opposing team using a right handed starting pitcher.
Before we begin, here is the common Royals lineup that I compared against
Aoki-Infante-Hosmer-Butler-Gordon-Perez-Moustakas-Escobar-Dyson
Top 10 Lineups
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Batting Order Frequency Table
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Note: The most common lineup ended up 0.56 wins per 162 games behind the most optimal lineup. Not too bad. The simulator liked batting Perez cleanup which the Royals did not do. The simulator also liked hitting Escobar second instead of Infante (basically switching them).
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Before we begin, here is the common Royals lineup that I compared against
Aoki-Infante-Hosmer-Butler-Gordon-Perez-Moustakas-Escobar-Dyson
Top 10 Lineups
| Lineup | Wins/162 GB |
|---|---|
| Aoki-Infante-Moustakas-Perez-Gordon-Escobar-Hosmer-Butler-Dyson | 0.000 |
| Aoki-Escobar-Moustakas-Perez-Gordon-Infante-Dyson-Butler-Hosmer | 0.065 |
| Aoki-Escobar-Moustakas-Perez-Gordon-Butler-Dyson-Infante-Hosmer | 0.111 |
| Aoki-Infante-Moustakas-Perez-Gordon-Escobar-Dyson-Butler-Hosmer | 0.143 |
| Aoki-Escobar-Moustakas-Perez-Gordon-Butler-Hosmer-Infante-Dyson | 0.164 |
| Aoki-Escobar-Hosmer-Perez-Gordon-Infante-Moustakas-Butler-Dyson | 0.166 |
| Aoki-Escobar-Moustakas-Perez-Gordon-Infante-Hosmer-Butler-Dyson | 0.207 |
| Dyson-Infante-Moustakas-Perez-Gordon-Escobar-Aoki-Butler-Hosmer | 0.238 |
| Aoki-Escobar-Moustakas-Perez-Hosmer-Butler-Gordon-Infante-Dyson | 0.308 |
| Moustakas-Escobar-Hosmer-Perez-Gordon-Butler-Aoki-Infante-Dyson | 0.354 |
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Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Aoki | 30 | 0 | 0 | 0 | 9 | 0 | 5 | 0 | 6 |
| Escobar | 0 | 32 | 0 | 0 | 0 | 11 | 0 | 7 | 0 |
| Moustakas | 4 | 0 | 26 | 0 | 5 | 0 | 10 | 0 | 5 |
| Perez | 0 | 3 | 0 | 39 | 0 | 5 | 0 | 3 | 0 |
| Gordon | 9 | 0 | 0 | 0 | 30 | 0 | 10 | 0 | 1 |
| Infante | 0 | 14 | 0 | 0 | 0 | 19 | 0 | 17 | 0 |
| Hosmer | 2 | 0 | 24 | 0 | 6 | 0 | 10 | 0 | 8 |
| Butler | 0 | 1 | 0 | 11 | 0 | 15 | 0 | 23 | 0 |
| Dyson | 5 | 0 | 0 | 0 | 0 | 0 | 15 | 0 | 30 |
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Note: The most common lineup ended up 0.56 wins per 162 games behind the most optimal lineup. Not too bad. The simulator liked batting Perez cleanup which the Royals did not do. The simulator also liked hitting Escobar second instead of Infante (basically switching them).
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Wednesday, January 14, 2015
How Optimal Was The Cardinals 2014 Lineup
My simulator is a good tool for looking at optimal batting orders. It can play tens of thousands and even millions (with a smaller set of games) of games while keeping the opponent static which can give you a good idea which lineups win more games. Originally, taking an idea from the "straight arrows" over at The Book Blog, I decided to take the 2014 Dodgers most common lineup, that one can find over at the Baseball Reference website and compare how well that lineup does against tens of thousands of other possible lineup permutations. Now I decided to move on to the St. Louis Cardinals mostly because I like doing this and the Cardinals have a very analytical friendly blog not one that spends endless hours discussing TV shows, taco trucks and their personal problems. I did set some filters to cut down on the permutations, like I only looked at lineups where the pitcher hit 8th or 9th and where the best hitters didn't hit 8th or 9th and the worst hitters didn't hit 3rd or 4th etc... I wanted to see how well one of the Cardinals most common lineups compared to what the simulator thought was the most optimal lineup. Of course you can't expect any manager to be implementing the most optimal lineup but you also don't want him to be giving away fractions of wins each game that can add up over a 162 game season. So down below, I list the Top 10 lineups along with the most common 2014 lineup in a table sorted by Wins/162 games. I also list a table showing the frequency of where each player batted in each of the top 50 lineups. I love the batting order frequency tables as they show you which players have a few dedicated positions in the order they should be hitting in and which players are more versatile in giving you an optimal lineup. I used 2014 final season stats as the input projections for each hitter because that is for the most part similar to the data that the manager went by. And I did all the simulations with the opposing team using a right handed starting pitcher.
Before we begin, here is the common Cardinals lineup that I compared against
Carpenter-Wong-Holliday-Craig-Molina-Adams-Peralta-Bourjos-Pitcher.
Top 10 Lineups
| Rank | Lineup | Wins/162 Behind |
|---|---|---|
| 1 | Peralta-Carpenter-Holliday-Adams-Wong-Bourjos-Molina-Craig-Pitcher | 0.000 |
| 2 | Peralta-Carpenter-Adams-Holliday-Wong-Molina-Craig-Pitcher-Bourjos | 0.081 |
| 3 | Bourjos-Carpenter-Holliday-Adams-Peralta-Wong-Molina-Craig-Pitcher | 0.092 |
| 4 | Peralta-Carpenter-Adams-Holliday-Wong-Bourjos-Molina-Craig-Pitcher | 0.118 |
| 5 | Holliday-Carpenter-Peralta-Adams-Wong-Molina-Craig-Pitcher-Bourjos | 0.119 |
| 6 | Holliday-Carpenter-Adams-Peralta-Wong-Molina-Craig-Pitcher-Bourjos | 0.158 |
| 7 | Bourjos-Carpenter-Peralta-Holliday-Adams-Wong-Molina-Craig-Pitcher | 0.161 |
| 8 | Carpenter-Holliday-Adams-Peralta-Wong-Molina-Craig-Pitcher-Bourjos | 0.162 |
| 9 | Carpenter-Wong-Peralta-Holliday-Adams-Bourjos-Molina-Craig-Pitcher | 0.206 |
| 10 | Wong-Carpenter-Holliday-Peralta-Adams-Bourjos-Molina-Craig-Pitcher | 0.216 |
And how did the Cardinals common lineup fair? Wel, it finished 2.07 wins/162 games worse than the top ranking lineup according to the simulator. Good thing that lineup wasn't actually used 162 times but it kind of gives you a general idea of how many wins the Cardinals manager may have been leaving off the table during the entire season if you trust the output of the simulator. When I did this for the Dodgers, Mattingly's most common lineup was only 0.84 wins/162 games off from the most optimal.
Batting Order Frequency Table
| 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | |
|---|---|---|---|---|---|---|---|---|---|
| Carpenter | 15 | 19 | 7 | 6 | 3 | 0 | 0 | 0 | 0 |
| Peralta | 5 | 5 | 11 | 9 | 7 | 10 | 3 | 0 | 0 |
| Holliday | 3 | 6 | 17 | 17 | 6 | 1 | 0 | 0 | 0 |
| Adams | 0 | 5 | 12 | 18 | 10 | 3 | 2 | 0 | 0 |
| Wong | 9 | 5 | 0 | 0 | 22 | 12 | 2 | 0 | 0 |
| Molina | 0 | 3 | 3 | 0 | 0 | 12 | 31 | 0 | 1 |
| Bourjos | 18 | 7 | 0 | 0 | 2 | 12 | 4 | 0 | 7 |
| Craig | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 42 | 0 |
| Pitcher | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 42 |
Player by Player Analysis
Leadoff: Matt Carpenter. Matheny bats Carpenter leadoff and the simulator agrees that that is a good spot for him but he would be a little better off hitting second not first. Good
Second: Kolten Wong. Matheny bats Wong second and the simulator doesn't think that is one of the top three places for him to hit. It is not a totally glaring mistake as the simulator does have Wong hitting second in the 9th most optimal lineup but a better selection can be made here. Below Average
Third: Matt Holliday. Matheny bats Holliday third and pretty much nails this one. The simulator thinks that Holliday is a good third or fourth hitter in this lineup. While Holliday does have some batting order versatility and could even slot into the second and fifth slots without deserving to be taken out behind the shed. Great
Cleanup: Allen Craig. Matheny bats Craig cleanup and as you know Craig had an awful season. To Matheny's credit he probably didn't know Craig was going to be this bad and stay this bad as long as he did but nonetheless batting Craig cleanup was not a good choice and if done enough times would be extremely costly. The simulator liked Craig batting 8th, in front of the pitcher. Bad
Fifth: Yadier Molina: Matheny bats Molina fifth and the simulator does not like him there at all. The simulator likes the slow legged and power hitting catcher batting seventh or sixth at best where he can knock in runs and not get knocked in himself. Bad
Sixth: Matt Adams. Matheny bats Adams sixth and the simulator thinks that is too low. Mostly because the simulator already knows how bad Craig is. The simulator likes Craig batting cleanup or in one of the other traditional power hitting slots (third or fifth). Bad
Seventh: Jhonny Peralta. Matheny bats Peralta seventh and maybe he didn't know at the time he was building these lineups that Peralta would be one of his better hitters in 2014. A look up above at the 'Batting Order Frequency' table and you really see how versatile Peralta is in this lineup. Peralta hits leadoff in three of the four top optimal lineups and the simulator think the third, fourth and fifth slots are his best. Good
Eighth: Peter Bourjos. Matheny puts the all glove not stick Bourjos eighth. From above the simulator thinks that spot should be reserved for Allen Craig. The simulator touts leadoff or ninth, which in and of itself is a second leadoff spot, as the most optimal placement for Bourjos. Bourjos is leadoff in 2 of the top ten lineups and bats ninth in 4 of the top ten lineups. There is often efficiency in batting the pitcher 8th if you have the right personnel to do it. Bad
Ninth: Pitcher. The simulator has the pitcher batting 9th in 84% of the Top 50 lineups. Good
Overall:
So overall Matheny did not do a very good job with this lineup but to his credit the simulator is using end of season (or after the fact) input projections. If Matheny was hitting Craig cleanup when it was obvious he wasn't very good then he is greatly to blame, otherwise he gets some slack. How much slack is up for debate.
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