![]() It can be used as either a hitter or a pitcher stat. Walk rate (BB%) is the proportion of plate appearances that end in a walk. Why BACON (called CTBA in article) is more useful than BABIP – Shawn Childs, Sports Illustrated A high BACON can be an indication that the batter makes consistently solid contact and/or uses his speed to beat out infield hits. BACON is very similar to BABIP, except home runs are also included. Thus, walks, strikeouts, and hit batsmen are not included in the calculation. How Both Luck and Skill Can Influence BABIP – Devan Fink, Beyond The Box Scoreīatting Average on CONtact (BACON) determines how often a batter gets in hit when he makes contact. However, in smaller samples, a high BABIP may be a result of luck.īABIP = (hits – home runs) / (balls in play – home runs )īABIP calculation – Piper Slowinski, FanGraphs A high BABIP can be an indication that the batter makes consistently solid contact and/or uses his speed to beat out infield hits. Thus, walks, strikeouts, hit batsmen, and home runs are not included in the calculation. Why We Should Not Rely on Batting Average – John Edwards, Sporting Newsīatting Average on Balls in Play (BABIP) determines how often a batter gets a hit when he makes contact and the ball stays in the field of play. Lesson on Batting Average – Baseball Hall of Fame website Any plate appearance that does not constitute an at bat, such as a walk, hit batsman, or sacrifice is filtered out of the formula. ![]() All hits, whether it is a single or home run, count the same. It measures the percentage of at bats a hitter takes that end in a hit. The importance of pitch location – Patrick Brennanīatting Average (AVG) is one of the most basic offensive stat. ![]() ![]() How pitch location impacts batted balls – Jonah Pemstein, FanGraphs The height and strike zone status are irrelevant.ĪLOC% = Pitches located on pitcher’s armside / pitches thrown Given a right-handed pitcher, If we were to draw an imaginary vertical line that splits the strike zone in half, aLOC% tracks the portion of pitches that land to the right of the line (and vise versa for a lefty). A pitcher with a high 2-Str O-Swing% likely has good putaway stuff.Ģ-Str O-Swing% = Pitches swung at out of the zone/ pitches thrown out of the zone (2-strike counts only)ĪLoc% measures the percentage of pitches located on the pitcher’s arm side. A hitter with a high 2-Str O-Swing% likely struggles with plate discipline, especially when behind in the count. It tells us how often a hitter chases pitches out of the zone, or how often a pitcher forces the opponent to chase a pitch out of the zone, exclusively with two strikes. If a pitcher has a high 2-Str% on his curveball, that means he is more likely to use it as a put away pitch than early in the count.Ģ-Str% (P) = Pitches of that pitch type thrown in 2-strike counts / total pitches thrown in 2-strike countsĢ Str O-Swing% can be either a hitter or pitcher stat. 2-Str% can also be used on an individual pitch level. Pitchers with high 2-Str% typically get ahead in the count often, leading to better results. For example, if a pitcher’s slider has a 25% 2-Str%, this means 25% of his two-strike pitches were sliders. Two-Strike Percentage (Pitcher) (2-Str%(P)) tells us how often a pitcher’s pitch is thrown faces a two strike count against all the other pitches they throw in a two-strike count. Using 2-Str% to Predict Pitcher Breakouts – Nick Gerli, Pitcher ListĪpplication of 2-Str% – Dan McNamara, Pitcher List Hitters with high 2-Str% typically either have high whiff rates and/or like to work counts.Ģ-Str% = Pitches seen in 2-strike counts / pitches seen For example, if a hitter has a 25% 2-Str%, this means 25% of the pitches he has faced have come with 2 strikes. Two-Strike Percentage (2-Str%) tells us how often a hitter faces a two-strike count or a pitcher arrives at a two-strike count. Get to know every advanced baseball stat, how they’re calculated, and relevant links to great research done inside the sabermetric community. Staff writer and data scientist Jeremy Seigel has gathered all our stats and created one massive encyclopedia to keep track of it, written in laymen terms. We house dozens of columns and tables on our player pages and it can be overwhelming to learn everything, from their context to their derivisions and why they actually matter. There are so many baseball stats flying around. ![]()
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