In baseball, wOBA (or weighted on-base average)[1] is a statistic, based on linear weights,[2] designed to measure a player's overall offensive contributions per plate appearance. It is formed from taking the observed run values of various offensive events, dividing by a player's plate appearances, and scaling the result to be on the same scale as on-base percentage. Unlike statistics like OPS, wOBA attempts to assign the proper value for each type of hitting event. It was created by Tom Tango and his coauthors for The Book: Playing the Percentages in Baseball.[3]

Usage

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In 2008, sabermetrics website FanGraphs began listing the current and historical wOBA for all players in Major League Baseball.[4] It forms the basis of the offensive component of their wins above replacement (WAR) metric. Sites such as The Hardball Times have studied wOBA and found it to perform comparably to or better than other similar tools (OPS, RC, etc.) used in sabermetrics to estimate runs.[5][6] The Book uses wOBA in numerous studies to test the validity of many aspects of baseball conventional wisdom.

The benefit of wOBA compared to other offensive value statistics is that it values not just whether the runner reached base but how.[7][8] Events like home runs, walks, singles, etc. are given their own weight (or coefficient) within the linear formula. The weighting is based on the increase in expected runs for the event type as compared to an out. The coefficients change each season[9] based upon how often each event occurs.

Because the coefficients are derived from expected run value, we can use wOBA to estimate a few more things about a player's production and baseball as a whole. When using the formula (shown below), the numerator side on its own will give us an estimate of how many runs a player is worth to his team. Similarly, a team's wOBA is a good estimator of team runs scored, and deviations from predicted runs scored indicate a combination of situational hitting and base running.[10]

Balls hit hard (i.e. with a high exit velocity) in the sweet spot produce higher wOBA.[11]

Historical versions of the formula

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Coefficients for each tracked outcome vary by year. A historical record of these coefficients can be found at FanGraphs.[9]

2023

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Per Fangraphs, the formula for wOBA in the 2023 season was:[9]

 

where:

—————

Original formula

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The formula below appeared in The Book.[12]

 

where:

Ranges for elite, very good, etc.

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The following table serves as an aggregate summary of various wOBA scales available online.[10][13]

wOBA Scale
Classification Range
Elite .400 and Above
Very Good .371 to .399
Good .321 to .370
Average .320
Bad .291 to .320
Very Bad .290 and below

Citations

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  1. ^ "The Language Of Fangraphs | FanGraphs Baseball". 11 January 2010. Retrieved 2018-12-07.
  2. ^ "Linear Weights - FanGraphs Sabermetrics Library". www.fangraphs.com.
  3. ^ "wOBA - Weighted On Base Average". www.insidethebook.com.
  4. ^ "The Joy of wOBA - FanGraphs Baseball". www.fangraphs.com. 25 November 2008.
  5. ^ "The great run estimator shootout (part 1) - The Hardball Times". www.fangraphs.com. 9 April 2009.
  6. ^ "The great run estimator shootout (part 2) - The Hardball Times". www.fangraphs.com.
  7. ^ "What is a Weighted On-base Average (wOBA)? | Glossary". Major League Baseball. Retrieved 2018-11-09.
  8. ^ "wOBA | FanGraphs Sabermetrics Library". www.fangraphs.com. Retrieved 2018-11-09.
  9. ^ Jump up to: a b c "Guts!". FanGraphs. Retrieved November 9, 2018.
  10. ^ Jump up to: a b Rogers, Mike (2010-01-19). "Saber 101: Weighted On-Base Average (wOBA)". Bless You Boys. Retrieved 2018-12-07.
  11. ^ Clemens, Ben (February 25, 2020). "A Sweet Spot by Any Other Definition". FanGraphs. Retrieved March 14, 2024.
  12. ^ Tango, Tom M. (28 April 2014). The book : playing the percentages in baseball. Lichtman, Mitchel G., Dolphin, Andrew E. [Place of publication not identified]. ISBN 978-1-4942-6017-0. OCLC 919473395.{{cite book}}: CS1 maint: location missing publisher (link)
  13. ^ "The Beginner's Guide To Deriving wOBA | FanGraphs Sabermetrics Library". 11 April 2016. Retrieved 2018-12-07.

References

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  • Tom Tango, Mitchel Lichtman, and Andrew Dolphin. The Book: Playing the Percentages in Baseball. Washington, D.C.: Potomac Books, 2007. ISBN 1-59797-129-4.