2015 Dallas Baptist Baseball Projections

Monday, December 15, 2014

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Click on the link to view the new team and player projections for the 2015 Dallas Baptist baseball season. You will have to scroll down to view the tables dedicated to Dallas Baptist.

The tables along with the estimated winning percentage will be updated periodically to reflect the most recent outlook.

2015 Dallas Baptist baseball projections


2015 Bradley Baseball Projections Now Up

Friday, November 7, 2014

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Click on the link to view the new team and player projections for the 2015 Bradley baseball season. You will have to scroll down to view the tables dedicated to Bradley baseball.

The tables along with the estimated winning percentage will be updated periodically to reflect the most recent outlook.



2015 Wichita State Baseball Projections Now Up

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Click on the link to view the new team and player projections for the 2015 Wichita State baseball season.

The tables along with the estimated winning percentage will be updated periodically to reflect the most recent outlook.



StatCast Playoff Data Breakdown

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Now that the baseball season is over I thought I would throw together a little data breakdown of the 2014 playoffs according to the public StatCast records available. I created a rough relational database that will allow me to run a few simple queries to give us an idea of what information the new system will be able to spit out on a daily basis (fingers crossed, next season). I built the database with the anticipation of adding to the records next year as more data is released. I hope, eventually, there will be complete statistics available for each play because in the current format there are many null values which drives me nuts, but it is what it is.

Seven tables make up the database that is designed to catch each play in it's entirety. The four main tables are BATTING, FIELDING, PITCHING, and RUNNING. This is where all of the new fancy data is stored. Now as to not get further into the weeds lets take a look at what we got.




The Average Royals Offense is Good Enough

Monday, September 8, 2014

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With September in full swing the Royals can finally see the playoffs within reach. They are 2 games ahead of the Detroit Tigers in the AL Central and according to Clay Davenport have a 73% chance of making the playoffs.

The Royals 2014 projections only explain half of the reason of why they are where they are in the standings right now. The other half has to do with how the Tigers have not lived up to their preseason estimates and that has a lot to do with Detroit's pitching. I am not going to get into all of those details at the moment. Instead we are just tackling the Royals offense.

We know the Royals pitching has been great; we know their defense has been even better, but what we underestimate is just how average their offense has been. Yes, I said average. Kansas City's pitching and defense could have been great this year but if just two or three players underperformed their pre-season expectations by a good amount then this season could have been a bust, (still could). I can see this being argued as just another angle in which to look at the statistics, but really the most consistent part of Kansas City's team has been their pitching and defense so it makes sense to look at KC's offense to understand how they have pulled this season off.

Their farm system was known before the season to be loaded with pitching talent and we were told that the talent would finally be contributing this season, but the offense has always been a bigger question mark. You hoped guys like Hosmer and Moustakas would start putting it together, but you could not count on that. Up to this point in their careers they have not shown true signs of consistency.

The Royals front office, and most fans, banked on their hitters outperforming their projections this season in order to catapult the team into playoff contention. What no one expected was for them to play as predicted and quite arguably slightly under those predictions and still be in the hunt.

The Royals offense holds a current R/G average of 4.01. I projected at the beginning of the season that they would have a R/G of 4.12 by seasons end. For the most part, the 2014 Royals offense has played just as forecasted. Sure we all expected more power from Billy Butler and we didn't expect Moustakas to flirt with the Mendoza line all year, but as far as overall production the forecast was spot on. Below is my predictions for the Royals 2014 hitting statistics by player.



And here is the current Royals hitters statistics as of 9-8-2014. This was downloaded from Baseball-Reference.com. Don't get glossy eyes, these two tables are meant for you to just browse at leisure to see for yourself how the Royals have met and only met offensive expectations. In this case, with 21 games to go in the season, average might just be good enough.



Batters' Salaries After an All Star Year Compared to Their Production

Thursday, August 21, 2014

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This post goes along with a previous post in which I found that "...an All-Star selection can increase a player's salary significantly; on average by $1,517,550." Read the previous post here. What I did not demonstrate in the previous post, but intend to explain in this post is how that increase in a player's salary the year after an All-Star team selection relates to their statistical performance in that same year.

I used the same data that I compiled for the previous post, which included the list of All-Stars from 2002 - 2013 and their salaries before and after they were selected to the All-Star team, and added those same players core season statistics. For this post I am only going to deal with the batters, therefore I deleted the pitchers from my dataset as to not skew the calculations.

What I found was somewhat alarming, but not all that surprising. As I mentioned before, a player's salary increases by about $1.5 million on average the year after they are an All-Star. When I eliminated the pitchers from this list I found that batters ordinarily see an increase in annual salary of $1,426,104; a little less, but still a significant increase. As you look at the table, you will see that although teams tend to pay their batters more for making the All-Star team they do not necessarily see an increase or even a sustained level of production the following year from those players.



With that being said, in the grand scheme of things a drop off of an average of 18.1 Runs Created from one year to the next could be nothing more than simple regression. There will be years in which a player over performs for whatever reason. This does not mean the player is "overrated" or that he won't have another good year in the future. It simply means that if a player is a consistent .750 OPS guy and he has a year in which his OPS is .820 it's safe to say the next season he would be due to regress.

Also, I did not include age in my query of this dataset, but it should not be ruled out. If I'm not mistaken, with exception to perennial All-Stars (i.e. Jeter), players tend to make the All-Star team during their prime year(s) meaning 25-28 year old. As a whole, this slight drop off in production might be nothing more than age taking its toll.

So back to the question I posed in the previous post on whether an increase in a player's salary for making an All-Star game is justifiable for teams based on the future production of that player. At least with regards to the All-Star batters I would have to say no. Even though the overall average decrease in Runs Created was minimal, 18.1, it was still a decrease. I'm not saying don't reward the player at all, but it seems much more suitable in this case for teams to pay one time bonuses to players instead of increasing their annual salaries. Why pay a player a higher salary and ultimately shrink your payroll that much more for a guy who performed well for 90 games or so? This allows more risk to creep back into a team's decisions. I say, leave the salary raises for current players that prove they can consistently perform at a high level for multiple seasons or save the money for free agent acquisitions.

The way the system works right now, a player can take advantage of a half seasons worth of good games or even a strong marketing campaign to elevate their annual salary by $1.5 million. Teams that have to scrape every penny to obtain and keep good players should pay close attention to these kinds of findings so they are not poorly allocating scarce resources. Its Economics 101.

(SQL query of Lahman database using the Salaries, Batting, and AllStarFull followed by data manipulation in R studio)


It Pays To Be An All-Star

Sunday, August 17, 2014

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I am fascinated with MLB player salaries (all sports salaries for that matter), and I wanted to know if it was worth anything to the player to be selected to an All-Star team. I know players typically have incentives built into their contract for achievements such as this, but they usually fall under the category of a one time bonus. What about their actual salary? Is it affected if the player makes an All-Star team?


The Logic

To bring this question to light, I first compiled a list of every player that has been selected to an All-Star team from 2002 - 2013. I chose to use this time frame to keep the salaries at a somewhat comparable level to today's. Go back to far in history and player salaries are significantly lower. Once I had my list of players, I found the average player salary for each of those years as well as an average for all years combined. I then gathered those same players' salaries for the year after they were an All-Star. A quick subtraction formula gave me the difference for each players' salary before and after they were an All-Star. I calculated the mean of those values to understand if player salaries increase or decrease the year after an All-Star team selection and by how much.

The Numbers

The total average salary of pre-All-Star players from 2002-2013 was $6,811,333. The total average salary of those same players for the year after they were an All-Star was $8,436,326. That's a difference of +1,624,993. The average difference was calculated to be $1,517,550. Below is a bar chart breaking down the difference in player salaries from year to year.


It seems that an All-Star selection can increase a player's salary significantly; on average by $1,517,550. What does this mean for MLB players and teams? For players, it means do everything you can to get on the All-Star team. This includes those goofy campaign videos players use to gain publicity and in turn get votes.

Lucory's campaign video: http://m.mlb.com/video/topic/8879232/v33770085

For teams, a player achieving All-Star status seems to be a catch 22. Or is it? Of course the team wants all of their players to play like All-Stars, but it will cost them in elevated salaries if they actually make the team. I don't think this bothers clubs though. For one, I am guessing (since I do not have the hard data) that teams gain some cheap branding from a player's involvement in the All-Star game and two, the increase in the players production on the field elevates his market value which would most likely demand an increase in salary.

For a future post I might look deeper into the average increase (or decrease) in WAR or RC by a player who makes the All-Star game compared to their increase in salary. This will help teams realize whether an increase in a players salary in truly warranted. It would also help teams determine how much to increase a players salary if it was found to be a worth while investment.


MLB StatCast Play Index Tables

Wednesday, August 13, 2014

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So in a previous post, where I compiled all of the StatCast data available on players released by MLBAM video demos, I promised I would try to find a good way to display and explain the tables I built and how I incorporated those into the Lahman database.

The Lahman database uses a playerID as a key to connect a majority of the the tables. I kept this same playerID in the new tables that I constructed to house the play-by-play data gathered from StatCast. I chose to create four tables. One for the batting element of each play, one for the fielding element, one for base running, and one for pitching. All four tables are connected by a playID. I am defining a play to be anything other than your typical ball or strike calls, including foul balls out of play, where nothing is affected besides the count. Depending on the type of play that occurs during the game, there might be a playID referenced in all four tables. A minimum of two tables will be used on each play of a game.

Example 1: Pitcher throws a pitch to the batter. The batter hits a fly ball to the left fielder. The left fielder catches it for the first out of the inning. Everything that StatCast could record about that play would be stored within the Play Index tables. In this case, the data would be stored in all tables except for base running (PlayIndexR).

The playID is determined by the month, day and year of the game, along with the two teams playing (teamID) and the number of the play in that game.

Example: The tenth play of the game on August 14, 2014 where the Boston Red Sox are playing the New York Yankees.

08 14 2014 010 BOS NYA = 08142014010BOSNYA
D  M  Yr     #     Team Team

The playerID's allow for each play to be unique for every individual player involved. This in turn allows for us to count statistics for each player to use for other purposes like finding season total numbers. The playID connects each part of the play. Without the playID it would be more difficult to query a full play. However, without the playerID, you couldn't use counting or rate statistics to calculate things such as a players career average and totals from certain StatCast data.

As you look at the list some fields will be self explanatory and others will require more clarification. Remember, each table collects a specific players data that was involved in a play. Going back to the example from above. All of the StatCast information regarding the batter who hit the fly ball to the left fielder will be stored in the Batting Play Index table (PlayIndexB). For that same play, all of the data relating to the catch by the left fielder will be stored in the Fielding Play Index table (PlayIndexF) and the pitchers information will funnel into the Pitching Play Index table (PlayIndexP). Since there was no base runner, the Base running Play Index table contains nothing for that play. All of this data is unique to each player; the batter, left fielder, and pitcher. All of their data is, however, connected by the playID which remains the same.

Browse the spreadsheet and think of ways in which you could make this more functional. By no means is this a one-all. In a later post I will break down each field in more detail.



The Forgotten Pitchers: Part 2 of 2

Tuesday, August 12, 2014

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Our journey down the forgotten memory lane continues with the final twelve pitchers on our list of pitchers who have only one career appearance without recording a single out. Just to remind everyone, who did not read Part 1 of 2, these are not position players who happened to pitch one time. Some were starters, others relievers, but all of them where pitchers who had one game, zero innings pitched careers. In Part 2 we continue to learn about the men who almost left no mark on the game...almost.


12. Jim "Lefty" Scoggins (1913)
Just like most of these forgotten players, little is known about Jim "Lefty" Scoggins besides that he was born in Killeen, TX and he appeared in his one game on August 26, 1913 for the Chicago White Sox. The White Sox finished in the middle of the American League pack that year with a record of 78 -74. In his one glorious game, Jim faced 2 batters gave up 1 walk and 1 run.

Career Pitching for Jim Scoggins
IP AB R ER ERA H BB WP HBP
0 2 1 0 Inf 0 1 0 0

13. Ed Coughlin (1884)
In a game against the Philadelphia Quakers on May 15, 1884, while playing for the Buffalo Bison of the National League, Ed Coughlin pitched in his one and only game as a major league baseball player. He pitched, or at least he tried to, to 5 batters. He gave up 3 hits and slung 2 wild pitches which led to 4 runs, 3 being earned. In that same game, Ed played a little outfield where he saw more success. He collected a hit and drove in a run so his career wasn't a total loss.

Career Pitching for Ed Coughlin
IP AB R ER ERA H BB WP HBP
0 5 4 3 Inf 3 0 2 0

14. Pat McGehee (1912)
In 1912 the Boston Red Sox moved into the cathedral known as Fenway Park. That same year Boston won the World Series, beating the New York Giants four games to three. That same season on August 23rd Pat McGehee pitched against the Washington Senators as a member of the Detroit Tigers. His success was minimal. Although he allowed no runs, he gave up 1 hit and 1 walk in 2 at bats and left without recording an out.

Career Pitching for Pat McGehee
IPABRERERAHBBWPHBP
020001100

15. Bill Moore (1925)
Thirteen years after Pat McGehee pitched in his only game for the Tigers, a twenty three year old Bill Moore took his only trip to the mound as a big leaguer; also as member of the Detroit Tigers. In the second game of the 1925 season Bill faced 3 White Sox batters, walked all 3, allowing 2 earned runs.

Career Pitching for Bill Moore
IPABRERERAHBBWPHBP
0322Inf0300

16. Marty "Buddy" Walker (1928)
Buddy played in Philadelphia, where he was born and raised, for the Phillies organization and his career consisted of one game, in which he lost, and never recorded an out. The line below tells you all you need to know. Fun Fact: Babe Ruth hit 54 home runs that same year.

Career Pitching for Marty Walker
IPABRERERAHBBWPHBP
0642Inf2300

17. Joe Brown (1927)
Joe Brown made a career out of minor league baseball from 1924 to 1930 with one lonely call up to the Chicago White Sox on May 17, 1927. That day Brown faced 3 Red Sox batters allowing 3 runs on 2 hits and 1 base on balls. The Red Sox finished dead last that year in the American League with a record of 51 - 103.

Career Pitching for Joe Brown
IPABRERERAHBBWPHBP
0333Inf2100

18. John Wood (1896)
In the same year that Utah became a state and Negro League great Oscar Charleston was born, John Wood played in his only major league baseball game for the St. Louis Browns. In a game against the New York Giants on May 9, 1896, Wood pitched to 4 batters allowing 1 run on 1 hit, 2 walks, and 1 hit batsman. He left the game with 0 innings pitched. That year the Browns had a dismal season finishing second to last place in the National League with a 40-90 record right behind the Brooklyn Bridegrooms.

Career Pitching for John Wood
IPABRERERAHBBWPHBP
0411Inf1201

19. Sid Benton (1922)
Sid Benton's career pitching line might be the meekest of them all. On April 18, 1922, while pitching for the St. Louis Cardinals in St. Louis, Sid came into the game to face 2 Chicago Cubs batters and walked them both. Fun fact: Roger Hornsby, a teammate of Benton's on that '22 Cardinals team, won the triple crown that season with a .401 BA, 42 HR, and 152 RBI.

Career Pitching for Sid Benton
IPABRERERAHBBWPHBP
020000200

20. Art Gardiner (1923)
One year after Sid Benton's one game stint, Art Gardiner put up his own single game career. On September 25, 1923, Art pitched to 2 Pittsburgh Pirates batters as a member of the Philadelphia Phillies. He walked one and allowed a hit before being pulled for teammate Jim Bishop. The Pirates won the game 18-5.

Career Pitching for Art Gardiner
IPABRERERAHBBWPHBP
020001100

21. Jay Parker (1899)
Just before the turn of the century, Jay Parker made his only appearance in the majors at West Side Park against the Chicago Orphans on September 27, 1899. Jay pitched for the Pittsburgh Pirates and that day faced three batters allowing 2 walks and hitting a batter. An interesting fact about that 1899 season, the Pittsburgh Pirates finished the season with nearly identical records. The Orphans were 75-73 and the Pirates were 76-73.

Career Pitching for Jay Parker
IPABRERERAHBBWPHBP
0322Inf0201

22. Doc Sechrist (1899)
Five months before Jay Parker played in his only major league game and in the same season, Doc Sechrist pitched in his only game for the New York Giants. Against the Washington Senators on April 28, 1899 Doc saw 2 batters and walked both. He ended his career with no official ERA because he did not allow a run but never recorded an out. He played in the minors until 1904, but never made it back to the show.

Career Pitching for Doc Sechrist
IPABRERERAHBBWPHBP
020000200

Not to Be Left Out: 

23.  Sam Mayer (1915)
Sam Mayer's career did not end in one game like that of his fellow pitchers on this list. Sam pitched in one game in the 1915 season for the Washington Senators. In that game he walked the first two batters he faced and was pulled before recording an out. The difference between Mayer and the other players on this list is that Sam's career extended for 22 more days. He played in the outfield for 11 games accruing 37 plate appearances, 7 hits and 1 dinger. However, it was his 1 game as a pitcher and short career that landed Sam Mayer on this list.

Career Pitching for Sam Mayer
IPABRERERAHBBWPHBP
020000200

(Statistics derived from a SQL query of the Lahman Baseball Database)


A Compilation of Public MLB StatCast Statistics

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There has been a lot of hype about the new MLBAM StatCast system; a player tracking/raw data machine. With all of this new data will come a need for more data analysis and most likely a better way to store and track data. I have manually compiled every piece of StatCast data currently available to the public through the various videos published on MLB.com demonstrating some of the impressive capabilities of the new system.

Some of this data came from the 2014 All-Star Game since Major League Baseball was using that stage to show off StatCast. I assume we might see more examples released by MLB come playoff time. I have included below a maneuverable spreadsheet demonstrating a few of the key data fields that might be collected for each play in a major league baseball game using StatCast. The database that I created for this new StatCast data includes four tables connected to the Lahman database which I use to query players' past statistics. These four tables are PlayIndexB (Batters), PlayIndexF (Fielding), PlayIndexR (Base Running), PlayIndexP (Pitching). This seemed to me to be the easiest way to implement the new statistics since I can connect them to playerID's that would allow me to JOIN other tables in the Lahman files. These tables are meant to store every play within each game of a season using a playID to connect plays from table to table. For example, if I were to query playID 7062014003 it would bring up all the players and data involved with the third play of the game on 7-6-2014 whether it be on the Batters, Fielding, Running, or Pitching table. This setup will also allow me to use counting and rate SQL formulas to easily understand a players season and career StatCast statistics.

It is important to note that the tables I built contain many more data points for each play of a game and I will display those in a later post, but for now  I am only highlighting some flashy data in the spreadsheets.

As you look over the numbers you will see some stars like Mike Trout (troutmi01), Andrew McCutchen (mccutan01), and Troy Tulowitzki (tulowtr01). As I stated before, I was limited to the stats that have been released by MLB from a few 2013-2014 regular season games as well as the 2014 All-Star Game so the data on some of these players are incomplete or non-existent. This was more of a project about using the data we know can be tracked to create workable tables that can be fused with other different databases; in my case I am morphing the new data with the Lahman baseball files. While we have little data to work with now, in the future I will be ready to incorporate lots of play-by-play StatCast stats into my database.

I suggest that you browse each spreadsheet to get a feel for the data.....



Ok, now that you have played around with the spreadsheets you might be thinking of unique ways to use these numbers to help evaluate players. I have an ongoing brainstorming blog post that lists ways in which teams/management can use StatCast to test the overall performance of players.

Just for fun let's see who ranks highest in some of these new statistical categories based on the micro amount of data we have.

Batters
Greatest Exit Velocity (off bat): Jon Jay, 102.1 mph
Greatest Max Speed from H to 1B: Dee Gordon, 20.9 mph

Fielding
Quickest Acceleration: Andrew McCutchen, 3.54 ft/sec2
Greatest Max Speed: Billy Hamilton, 23.3 mph
Highest Route Efficiency: Andrew McCutchen, 99.7%
Quickest Release: Aramis Ramirez, .48 sec
Fastest Catchers Pop Time: Anthony Recker, .6 sec
Greatest Catchers Velocity: Anthony Recker, 78.8 mph

Base Running
Quickest First Step (on steal): Billy Hamilton, -.18 sec
Quickest Acceleration: Billy Hamilton, 2.17 ft/sec2
Greatest Max Speed: Billy Hamilton, 21.2 mph

Pitching
Longest Extension: Edison Volquez, 84 in
Actual Velocity: Edison Volquez, 95.2 mph
Largest Difference between Perceived and Actual Velocity: Francisco Rodriguez, 2.9 mph
Greatest Spin Rate: JJ Hoover, 2582 rpm

These stats really don't mean much since they're only taken from a few plays, but imagine what we could come up with if we had every games' stats. Also, think about how we could correlate some of this data with other metrics. How does a pitchers Spin Rate effect his Fly Ball or Ground Ball rate? How does a players Lead Length or First Step affect his Stolen Base percentage? Does a batters average Exit Velocity or Launch Angle have any correlation with his BABIP or OPS? This could help players know what they need to work on. A batter will now know if he needs to work on his acceleration out of the box and pitcher will know if his extension is causing him to throw more balls.

All of these things will be dealt with as soon as we get more data. I am trying to increase my "First Step" rate by creating tables to house the new data before it is available. In a future post I will hopefully come up with a good way to demonstrate all of the fields in my PlayIndex tables so that others can provide feedback. By no means do I think I have hit the nail on the head with this first attempt to store the new data, but I at least wanted to get the ball rolling.


The Forgotten Pitchers: Part 1 of 2

Thursday, July 31, 2014

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Thousands of pitchers have played major league baseball. Most of us only remember the greats and rightly so. Hall of Famers like Walter Johnson, Sandy Koufax, and Greg Maddux. These are great pitchers and should be remembered. But what about all the others? There are a few that have slipped thru the cracks that I find very interesting.

This is a list of all MLB pitchers in history who have only one career appearance and recorded no outs in that appearance. These are not position players who happened to pitch one time. Some were starters others relievers, but all of them where pitchers who had one game, zero innings pitched careers. Take a trip back in history and learn how a few forgotten players contributed to the game in their own little way.


1. Bill Childers (1895)
Not much is known about Bill Childers except that he was born in St. Louis, MO and his career professional pitching line is one of the worst of all time. Bill entered his one and only game on July 27, 1895 and 2 hits, 6 walks, 3 wild pitches and 6 earned runs later his career was over. His final ERA was "Infinite".

Career Pitching for Bill Childers
IP AB R ER ERA H BB WP HBP
0 8 6 6 Inf 2 6 3 0

2. Doc Hamann (1922)
Doc was one of many minor leaguers that Cleveland Indians manager Tris Speaker brought up to play in the game against the Boston Red Sox on September 21, 1922. Speaker thought it was a good opportunity for the Indian fans to get a look at the clubs prospects. However, for Doc this would be the first and last major league game he would ever play in. Doc's pitching line includes 7 batters faced, 3 hits, 3 walks, and 1 hit by pitch. He left the game allowing three runs, all earned, without recording a single out. This concluded his pro ball career.

Career Pitching for Doc Hamann
IP AB R ER ERA H BB WP HBP
0 7 6 6 Inf 3 3 1 1

3. Mike Palagyi (1939)
Mike played and pitched in his only major league game against the Boston Red Sox on August 18, 1939 as a member of the Washington Senators. In that game he faced three Hall of Fame players in Ted Williams, Jimmy Foxx, and Joe Cronin. I would give him credit for this, but he walked two of them and beaned the other before finally being pulled from the game. He never pitched or played again.

Career Pitching for Mike Palagyi
IPABRERERAHBBWPHBP
0433Inf0301

4. Fred Bruckbauer (1961)
Mr. Bruckbauer was a good pitcher for the Minnesota Golden Gophers in the late 50s, but did not find such success in his one appearance for the Minnesota Twins. On April 25, 1961, Fred made a relief appearance against the Kansas City Athletics at Municipal Stadium. It would be his last. He saw 4 batters gave up a hit to three of them and walked the other. He retired and went down in history with an infinite ERA.

Career Pitching for Fred Bruckbauer
IPABRERERAHBBWPHBP
0433Inf3100

5. Jim Schelle (1939)
A native of Baltimore, Maryland, Jim Schelle made his professional baseball debut on July 23, 1939 with the Philadelphia Athletics. The Athletics were playing the Detroit Tigers and Schelle came in as relief in the fourth inning. He allowed all five batters he saw to reach base allowing three of the players to score. He was then pulled, before recording an out, and sent back to the minors were he would end his career.

Career Pitching for Jim Schelle
IPABRERERAHBBWPHBP
0533Inf1301

6. Frank Dupee (1901)
Dupee saw success as a semi pro pitcher in the New England League before joining the Chicago White Stockings in the summer of 1901. Dupee was given the start on August 24, 1901 against the Baltimore Orioles. Clinging to a half game lead over the Boston Americans, Chicago was dealing with several injuries to key pitchers and were in desperate need of a solid performance from their new starter Dupee. He did not deliver. Dupee walked the first three batters he faced and was replaced. All three of those runners ended up scoring and the White Stockings went on to lose the game. Dupee never played in another major league game.

Career Pitching for Frank Dupee
IPABRERERAHBBWPHBP
0333Inf0300

7. Will Koenigsmark (1919)
A native of Illinois, Will Koenigsmark, right handed pitcher for the St. Louis Cardinals, made his only appearance in the majors on September 10, 1919. He allowed 2 hits, 1 walk, and 2 earned runs. What a career!

Career Pitching for Will Koenigsmark
IPABRERERAHBBWPHBP
0322Inf2100

8. Bill Ford (1936)
On the last day of the 1936 season, the Boston Bees sent Bill Ford to the mound as the starting pitcher going against the Philadelphia Phillies. Ford could not retire a single batter walking all three he faced. He was replaced by Guy Bush who pitched all nine innings and won the game. Bill Ford's stat line was not found until 2003.

Career Pitching for Bill Ford
IPABRERERAHBBWPHBP
0322Inf0300

9. Lou Bauer (1918)
At the young age of 19, Lou Bauer appeared in his one and only game for the Philadelphia Athletics on August 13, 1918. It did not go well. His game/career line includes 2 batters faced, 2 walks, and 1 earned run. Seems like he should have got another chance.

Career Pitching for Lou Bauer
IPABRERERAHBBWPHBP
0221Inf0200

10. Gordie Sundin (1956)
Gordie Sundin's lone appearance came on September 19, 1956 for the Baltimore Orioles. Baltimore was behind 8-1 to the Detroit Tigers when Sundin came into the game. He walked both batters he saw and was subsequently pulled from the game. He was charged with 1 earned run. This outing was the end of his MLB career. He went back to the minors and retired 5 years later.

Career Pitching for Gordie Sundin
IPABRERERAHBBWPHBP
0211Inf0200

11. Larry Yount (1971)
Larry Yount, older brother to Hall of Famer Robin Yount, holds one of the most peculiar baseball records of all time. Larry is the only pitcher in MLB history to appear on the official score book without ever facing a batter. On September 15, 1971, while playing for the Houston Astros, Yount was announced as the pitcher in the ninth inning against the Atlanta Braves, but experienced soreness in his arm while warming up and was removed before he threw an official pitch. After the game he went back to AAA. Larry played for 8 years in the minor leagues, but was never able to make it back to the show. Meanwhile, his brother Robin had more hits than anybody in the 1980's. Sorry Larry.

Career Pitching for Larry Yount
IPABRERERAHBBWPHBP
000000000

Go to The Forgotten Pitchers: Part 2 of 2

(Statistics derived from a SQL query of the Lahman Baseball Database)


Brainstorming MLBAM StatCast (Ongoing)

Monday, July 28, 2014

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Here are my thoughts on how teams could use the new MLBAM StatCast player tracking system to evaluate players performance. I have broke it down by a few broad baseball functions (Base running, Hitting, Fielding Infield, Fielding Outfield, and Pitching). I will update this post from time to time with new ideas.

Base runners
1. Top speed from home to first base, second base, and third base
2. Running path from home to first base, second base, and third base
3. Players top speed during a stolen base
4. Average length of a base runners lead
5. Players top speed from any base to any base
6. Players running path from any base to any base
7. Create a statistic for a players top average speed from each base to any base
8. Categorize base running stats by average top speed, average lead length
   i. Determine the correlation of avg top speed to stolen base pct and avg lead length to stolen base pct
   i. Determine correlation of avg top speed to extra base hits and running path to to extra base hits
9. Determine how many feet it takes for a player to reach top speed (Acceleration)
10. Determine optimum distance for a player to reach top speed while stealing a base 
11. Determine optimum distance for a player to reach top speed while running from one base/plate to another base. (Ex. Runner should reach top speed on a double when he is 50 feet away from 2nd base)
12. Determine optimum distance for a runner to begin their slide based on their average top speed, distance to reach top speed, and height of runner.
13. Determine which sliding path is most efficient (Ex. inside part of base, out side, straight)
14. Determine optimum base runner lead for a safe steal and slide back
15. Calculate a players average batted ball speed
   i. Correlation between avg batted ball speed and BA, SLG, OBP, extra base hits, HR, 1B, 2B, 3B
   i. Batted ball speed and the age of the player
16. Calculate a players average launch angle
   i. Correlation between a players avg launch angle and BA, SLG, OBP, extra base hits, HR, 1B, 2B,         3B (Can a player correct or improve his launch angle?)
17. Calculate a players average hang time of batted balls
   i. Correlation between a players hang time and BA, SLG, OBP, extra base hits, HR, 1B, 2B, 3B
18. Determine average first step of a base runner stealing a base
19. Determine average acceleration of a runner stealing a base

Hitting
1. Average batted ball distance
   i. Determine correlation from average batted ball distance and number of extra base hits, batting average, slugging pct, on base pct
   i. Determine average batted ball distance changes with the age of player
   i. Determine average batted ball distance for each MLB stadium
   i. Determine average batted ball distance for each stadium for each month (home and or away)

Fielding Infield
1. Most efficient place to stand when receiving a throw down from the catcher (be able to know the most used slide path of base runners)
2. Determine average route efficiency for each player
3. Percentage of balls fielded cleanly and thrown out (infield) (Ex. A player might have good range to get to the ground ball, but is he able to throw the runner out?)
4. Average distance a fielder travels to field ground ball cleanly (ex. compare good range with bad)
5. Calculate a players average first step time
6. Average catcher pop time
7. Average catcher arm strength in mph
8. Average infielders arm strength on throws to first
9. Average flight path of a catchers thrown ball (more to the left, right, or straight to 2nd base)
   i. Can throw down path demonstrate if a catcher is successful?

Fielding Outfield
1. Determine average route efficiency for each player
2. Average distance a fielder travels to field ball cleanly (ex. compare good range with bad)
3. Calculate a players average first step time
4. Calculate a players average top speed while fielding a line drive, fly ball, ground ball
5. Calculate a players average acceleration to the ball
6. Average arm strength on attempted assist throws.

Pitching
1. Determine correlation between a pitchers regular velocity and extension
2. Determine correlation between a pitchers perceived velocity and extension
3. Does spin rate determine where a ball might be hit?
4. Does spin rate correlate with the velocity of the ball?


Total MLB Player Salaries by University from 1985-2013

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(SQL query of Lahman database using Salaries table and Schools table)



ChyronHego and TrackMan™ Press Release About New StatCast Technology

Thursday, July 10, 2014

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The following press release was taken from ChyronHego.com.

MELVILLE, N.Y. — THURSDAY, APRIL 3, 2014
ChyronHego and TrackMan™, a leading provider of radar technology for sports, today announced a strategic partnership in baseball player and ball tracking technology. 
The combined best-of-breed solution is a non-invasive offering that provides quality data for player evaluation, coaching and fan experience analysis in a converged infrastructure. Teams can now develop customized analytics while maintaining their own unique process. 
“The ChyronHego and TrackMan partnership is a breakthrough in data gathering for the sport of baseball,” said Johan Apel, president and chief executive officer at ChyronHego. “Coaches are now able to analyze individual player movements and track the ball for every play and our real-time data provides fan experience executives with never before seen opportunities to engage fans in this uniquely data-driven sport.”
“The Big Data trends driven by cloud and mobility are creating a new style of sports analysis that is transforming what coaches and fans expect and need from sports technology,” said John Olshan, general manager at TrackMan Baseball. “I’m thrilled to have Trackman and ChyronHego work together to help the sport tackle these exciting challenges. By jointly developing and leveraging each other’s technology, we will deliver the highest standard in data performance and reliability. “  
ChyronHego and TrackMan will continue to develop and market the technology to a broad range of baseball teams and leagues around the globe. The combined solution has already been successfully deployed in multiple U.S. stadiums. 

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