White Sox News

Does the White Sox April Performance Change Anything?

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CHICAGO, ILLINOIS - APRIL 26: Tim Anderson #7 of the Chicago White Sox celebrates after hitting a walk-off home run in the 9th inning against the Detroit Tigers at Guaranteed Rate Field on April 26, 2019 in Chicago, Illinois. The White Sox defeated the Tigers 12-11. (Photo by Jonathan Daniel/Getty Images)
CHICAGO, ILLINOIS - APRIL 26: Tim Anderson #7 of the Chicago White Sox celebrates after hitting a walk-off home run in the 9th inning against the Detroit Tigers at Guaranteed Rate Field on April 26, 2019 in Chicago, Illinois. The White Sox defeated the Tigers 12-11. (Photo by Jonathan Daniel/Getty Images) /
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BALTIMORE, MD – APRIL 22: James McCann #33 of the Chicago White Sox celebrates with teammates after hitting a three-run home run in the fifth inning against the Baltimore Orioles at Oriole Park at Camden Yards on April 22, 2019 in Baltimore, Maryland. (Photo by Will Newton/Getty Images) /

A breakdown of the White Sox month of April performance and a comparison of that performance to other 21st century teams.

There is an old statement about April baseball with which many baseball fans are familiar. “A division can’t be won in April, but it can be lost.” The source of this long-accepted quote seems to be lost to history, but it has been repeated many times.

The next question to ask is how true is this? How important is April performance? What end-of-April winning percentage dooms a team? More importantly for our purposes, what does the White Sox’s current April performance mean in terms of postseason odds, or even the odds of making 2019 a winning year, their first since 2012?

First of all, a basic understanding of correlation in statistics is required. Many of these stats use what is called a correlation coefficient, which analyzes how closely related two sets of data are. The number can be anywhere from negative one to positive one. The closer number is to positive one, the closer the correlation.

For example, if two sets of data were “1, 2, 3, 4” and “2, 4, 6, 8” the data is perfectly correlated. This would mean a correlation coefficient of positive one. If a number from the first set increases, the number from the second set is increasing at the same rate consistently. As for a negative correlation, if the numbers were “1, 2, 3, 4” and “-2, -4, -6, -8” then the correlation would be -1. The closer to one or negative one, the more closely related the data is. If two sets of data have a correlation coefficient near 0, there is no real relation between the two sets of data.

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