This site is currently beta and considered a work in progress.
The purpose of the data model shown here is to provide reference to anything related to teams, players and games for Major League Baseball during current year and for all years after 1900.
Currently this About tab is the last to get attention. Explanations will be added incrementally throughout the off season. Right now for more information as to the development of the data model behind this site see baseball.brandylion.com
WAA stands for Wins Above Average. This has nothing to do with the similarly named WAA value used in computing WAR. It is a number that represents wins minus losses (W – L). WAA applies to teams and players that make up that team.
Here is a simple example calculation for teams. The 2012 Chicago Cubs had a record of 61-101 for the season which would translate into a real team WAA of:
WAA = W – L = 61 – 101 = -40
Not too complicated! At the end of a season this value is used to determine which teams go to the playoffs.
This data model assigns WAA value to players where the sum of player WAA equals real team WAA. Players who play for multiple teams will have a separate WAA value for each team. In the above example the sum of the 2012 Chicago Cubs player WAA will equal -40. This means many Cubs players with negative value. Losing 101 games in a season is a team effort as much as winning 101 games in a season. Value systems like WAR avoid showing negative value for players unless it’s truly egregious.
A completely average team will end up with an 81-81 record which translates into a WAA = 0 which is better than half the teams in MLB. In 2019 Cy Young winner Justin Verlander was #1 player in MLB for all players, hitters and pitchers, with a WAA = +9.7 or around +10 for simplicity. If all players on the Astros played completely average except for Verlander the Astros would have finished 2019 with a record of 86-76 which is +10 real team WAA.
The 2019 Astros however won 107 games in 2019 for a real team WAA = +52 which means there were many top of the league players on their roster which you can see here.
Player rank uses WAA as a weighting factor and accompanies all player records to provide context. Player value lost for every run given up by a pitcher is gained by the hitter and runner. Value lost for every out a hitter makes is gained by a pitcher. Pitcher and hitter value are symmetrical so they can be ranked together.
This model does not separate AL and NL. It compiles data and ranks all players in MLB together. For AAA, AA, and A+ minor leagues it compiles data for all affiliated franchise teams and players together in each league. Player value does not transfer between leagues.
Ranking allows for somewhat direct comparison between this data model and WAR. WAR however is not symmetrical between pitchers and hitters as it assigns 60% of its total value to hitters and 40% to pitchers. In WAA sum total value for all players is zero exactly because the sum value of all real team WAA is exactly zero. For every win a team makes another team loses and for every run scored the opponent team counts a run scored against.
The sum of WAR values each season adds to 1000. The WAR and WAA numbers are not comparable but ranks for each system can be directly compared.
In modern 30 team league ranks for both models show top and bottom 200. Players must reach a minimum 1.25 WAA in either direction to be ranked which means it takes a few months of playing time to fill out these lists. Going back in time there were less teams and for most of the 20th century MLB only had 16 teams, a little over half of the 30 teams today. A player in the top 50 in 1940 would be considered in the top 100 in modern baseball. Thus, ranks top off at 110 in 16 team seasons and ramp up to 200 as MLB expanded over the years.
WAR numbers are conveniently accessible throughout this site for quick comparison between the two value systems. The inspiration behind development of this data model was finding out in 2012 WAR ranked Chicago Cubs player Darwin Barney #37 in MLB for both pitchers and hitters which seemed incredible considering the Cubs finished the season 61-101. This model ranked Barney #126 in the bottom 200, a list no one wants to be #1.
More to come ...