Money Ball And Data Analytics In Baseball

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Abstract

Oaklands A’s has a secret success story related to their most consecutive win in Baseball History. Michael Lewis owned a team with low budget of 38 Million Dollars and with poor management of team. General Manager Billy Beane with a high vision used statistical analysis along with Economist Peter Brand which lead them to win 20 Games back to back without spending huge amount of money behind players. Oakland A’s selected the best player according to the statistics of player with keeping high base percentage value .Oaklands A’s with this statistical technique created history with most back to back win in baseball.

Challenges for Oaklands A’s

Oaklands A’s were in the hands of General Manager Billy Bean and they were losing the matches at home in the best of five series because of low budget to the highest budget team of 120 Million dollars Yankees. Oaklands A’s lost all the best player because of the low pay roll to high pay roll team such as Yankees and Red Sox. Oakland A’s faced a big challenge when the were losing their top player Giambie and Jhonny Damon by 8 million dollars.

Oakland A’s did not have pitcher who can take up to the mark of winning the matches. Oakland A’s had problem in understanding their player capabilities and always lead to trade their good player in the hunt of win. Oakland A’s spending a money on unnecessary player which valued less then what they were getting as pay roll.

Oakland A’s always used quirky reason to take a player out from a team or trade them off Poor Management of the team also lead to failure to win the matches because they tried to get player regarding their social life. No statistical data was used by the team management to know proper form of a existing or trading player which lead them to lose matches.

How Oakland A’s had overcome challenges

General Manager Billy Beane used sabermetrics which was developed by James which changed the fortune of Oakland A’s. Billy Beane meeting up with the Peter Brand who was working for Cleveland Indians who was economist which helped Billy Beane to understand proper statistics of player.

Peter Brand Evaluated using 2000 player which helped Oakland A’s to select their top 25 player with low pay roll. After selecting player, they were still doing statistical analysis for trading of the existing player.

Oakland A’s selected a player with high on base percentage and low budget using Peter Brand mathematics and program. Oakland A’s selected 4 players which replaced Giambi, Isringhausen and Damon using on base value they were Jeremy, David Justice, Scott Hatterberg, Chad Bradford. As Oakland A’s faced problem of pitcher Chad Bradford was great finding who had unusual action which lead problem to batter to hit.

Oakland A’s major replacement did not work at the start which lead them to lose the matches which kept them at bottom of the table.

Outcome of Analytics

Analytics helped Oakland A’s to select top 25 player which would get fit into their low budget and get them a win. Oakland A’s made a change in their team using statistical analysis which lead them to win 7 in a row back to back series win in Boston and New York in Mid of June 2002. Oakland A’s wins made them to be ranked number one in the table.

Oakland A’s further replaced Pane and Jeremy based on recent analytics with Ricardo Rincon and Mabry to win further matches. Oakland A’s replacement helped them to win straight win 17 games which created history after 1953 as they were unstoppable to win further matches. On September 2004, created history of longest consecutive wins of 20 games when Hatterberg hits a home run which was almost took 103 years. 20th Consecutive game also made them to stand for elimination match, but statistical analysis did not played role in 2002 ALDS game which was elimination in which they lost as match against Minnesota Twins.

Reference

Sony Picture Entertainment (Firm) 2012
https://www.theatlantic.com/entertainment/archive/2011/09/the-many-problems-with-moneyball/245769/
https://www.mx3metrics.com/blog/2016/3/14/moneyball-overcoming-resistance

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Money Ball And Data Analytics In Baseball

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