O-Swing%, sometimes called Chase Rate is a plate discipline metric. The calculation is the number of out of the zone pitches a hitter swings at divided by the total number of out of the zone pitches the hitter faces. This statistic shows you what hitters are best and worst at identifying strikes and balls.
The league average is 30%, with the lowest values being just above 14% and the highest values being just below 52%. Here is a histogram of every O-Swing% posted over the last five years (with a 200 plate appearance minimum). The swing percentages are on the x-axis, and the frequencies are on the y-axis. The higher the bar, the more hitters there were that fell into that range of o-swing%.
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The most disciplined hitters will still swing at a ball something like 20% of the time, and even the most free-swinging hitters will lay off well over half of the balls they see.
So what good is this? The answer lies in correlation. Let’s explore with a scatter plot.
This scatter plot plots each hitter’s o-swing% on the x-axis and their walk rate on the y-axis. This is a good visual way to see how one variable affects another. You can see from this visual that as o-swing% increases, the walk rate typically decreases. Of course, that makes intuitive sense, since the way to draw a walk is to not swing at pitches out of the zone.
O-Swing%, sometimes called Chase Rate is a plate discipline metric. The calculation is the number of out of the zone pitches a hitter swings at divided by the total number of out of the zone pitches the hitter faces. This statistic shows you what hitters are best and worst at identifying strikes and balls.
The league average is 30%, with the lowest values being just above 14% and the highest values being just below 52%. Here is a histogram of every O-Swing% posted over the last five years (with a 200 plate appearance minimum). The swing percentages are on the x-axis, and the frequencies are on the y-axis. The higher the bar, the more hitters there were that fell into that range of o-swing%.
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The most disciplined hitters will still swing at a ball something like 20% of the time, and even the most free-swinging hitters will lay off well over half of the balls they see.
So what good is this? The answer lies in correlation. Let’s explore with a scatter plot.
This scatter plot plots each hitter’s o-swing% on the x-axis and their walk rate on the y-axis. This is a good visual way to see how one variable affects another. You can see from this visual that as o-swing% increases, the walk rate typically decreases. Of course, that makes intuitive sense, since the way to draw a walk is to not swing at pitches out of the zone.
There are two obvious ways to use this for fantasy purposes.
- Find high on-base percentage hitters. There are hitters out there that had a low o-swing% but still did not come in very low at walk rate. That fact could be due to some randomness and should correct over time. You see a few dots on there for players that were only chasing pitches about 8% of the time, but still had an average walk rate (6%-10%). That is a very rare occurrence and probably would never happen again for that hitter.
- Identify possible breakouts. The very best hitters in the league all have an incredible batter’s eye. A huge key to hitting is identifying the type and location of the pitch as fast as possible. This ability will manifest in a hitter not swinging at balls out of the zone. It is useful to check these plate discipline metrics for young players, that can give you a hint to what their true upside is.
There are two statistics very similar to this one. Z-Swing% (zone swing rate) is the same exact thing, except it is measuring pitches thrown inside of the strike zone. Swing% is just what percentage of the time a hitter swings at all pitches. All of these statistics are very useful for going a little bit deeper in player evaluation.
If you enjoyed this post and want to learn more about advanced statistics, check out our sabermetrics page.
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Jon Anderson is a featured writer at FantasyPros. For more from Jon, check out his archive and follow him @JonPgh.
