wOBA

{{Short description|Baseball statistic}}

{{lowercase}}

In baseball, wOBA (or weighted on-base average){{Cite web|url=https://www.fangraphs.com/blogs/the-language-of-fangraphs/|title=The Language Of Fangraphs {{!}} FanGraphs Baseball|date=11 January 2010 |access-date=2018-12-07}} is a statistic, based on linear weights,{{cite web|url=https://www.fangraphs.com/library/principles/linear-weights/|title=Linear Weights - FanGraphs Sabermetrics Library|website=www.fangraphs.com}} 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.{{cite web|url=http://www.insidethebook.com/woba.shtml|title=wOBA - Weighted On Base Average|website=www.insidethebook.com}}

Usage

In 2008, sabermetrics website FanGraphs began listing the current and historical wOBA for all players in Major League Baseball.{{cite web|url=http://www.fangraphs.com/blogs/index.php/the-joy-of-woba/|title=The Joy of wOBA - FanGraphs Baseball|website=www.fangraphs.com|date=25 November 2008 }} 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.{{cite web|url=https://www.fangraphs.com/tht/the-great-run-estimator-shootout-part-1/|title=The great run estimator shootout (part 1) - The Hardball Times|website=www.fangraphs.com|date=9 April 2009 }}{{cite web|url=https://www.fangraphs.com/tht/the-great-run-estimator-shootout-part-2/|title=The great run estimator shootout (part 2) - The Hardball Times|website=www.fangraphs.com}} 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.{{Cite web|url=https://www.mlb.com/glossary/advanced-stats/weighted-on-base-average|title=What is a Weighted On-base Average (wOBA)? {{!}} Glossary|website=Major League Baseball|language=en-US|access-date=2018-11-09}}{{Cite web|url=https://www.fangraphs.com/library/offense/woba/|title=wOBA {{!}} FanGraphs Sabermetrics Library|website=www.fangraphs.com|access-date=2018-11-09}} 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{{Cite web |title=Guts! |url=https://www.fangraphs.com/guts.aspx?type=cn |access-date=November 9, 2018 |website=FanGraphs}} 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.

Balls hit hard (i.e. with a high exit velocity) in the sweet spot produce higher wOBA.{{cite news|first=Ben|last=Clemens|title=A Sweet Spot by Any Other Definition|date=February 25, 2020|work=FanGraphs|url=https://blogs.fangraphs.com/a-sweet-spot-by-any-other-definition/|access-date=March 14, 2024}}

Historical versions of the formula

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

= 2023 =

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

wOBA=\frac{(0.697*NIBB) + (0.727*HBP) + (0.855*\mathit{1}B) + (1.248*\mathit{2}B) + (1.575*\mathit{3}B) + (2.014*HR)}{AB + BB - IBB + SF + HBP}

where:

—————

= Original formula =

The formula below appeared in The Book.{{Cite book |last=Tango, Tom M. |url=https://www.worldcat.org/oclc/919473395 |title=The book : playing the percentages in baseball |others=Lichtman, Mitchel G., Dolphin, Andrew E. |date=28 April 2014 |isbn=978-1-4942-6017-0 |location=[Place of publication not identified] |oclc=919473395}}

wOBA=\frac{(0.72*NIBB) + (0.75*HBP) + (0.90*\mathit{1}B) + (0.92*RBOE) + (1.24*\mathit{2}B) + (1.56*\mathit{3}B) + (1.95*HR)}{PA}

where:

Ranges for elite, very good, etc.

The following table serves as an aggregate summary of various wOBA scales available online.{{Cite web|url=https://www.blessyouboys.com/2010/1/19/1258772/saber-101-weighted-on-base-average|title=Saber 101: Weighted On-Base Average (wOBA)|last=Rogers|first=Mike|date=2010-01-19|website=Bless You Boys|access-date=2018-12-07}}{{Cite web|url=https://www.fangraphs.com/library/the-beginners-guide-to-deriving-woba/|title=The Beginner's Guide To Deriving wOBA {{!}} FanGraphs Sabermetrics Library|date=11 April 2016 |access-date=2018-12-07}}

class="wikitable"

|+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

{{Reflist}}

References

  • 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}}.

{{Baseball statistics}}

Category:Batting statistics