An Alternative Method to Judge Baseball Hitting

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The Hitting Evaluator

(and Batting Average Predictor)

traing effectively for baseball using the wiffle ball

How I Judge Baseball Hitting

Baseball is a game of numbers, with numbers used to evaluate fielding and hitting performance as well as all other aspects of the baseball game. To get "good numbers" you need a large enough statistical base for the numbers to mean anything.

For example, in a 75 or 100 At Bat season - typical of a high school spring season, it is possible to get batting averages of players that are not really reflective of the players real ability. Average hitters can sometimes look like "all stars" if they get off to an unusually good start or get a string of "lucky" breaks where ground balls just seem to find every hole in the infield and "bloopers" all seem to drop in for hits. Conversely, a good player who seems to locate every infielder's glove with his line drives for a streak over a few games, will look like a very average hitter if you are only viewing the player's batting average.

There is a better way to evaluate a hitter's performance which takes into account how the ball is hit and can give you a basis to estimate the player's batting performance and average as it will "level out" over a longer and larger statistical base. After all, the hitter (player #1) who goes 0 - 4, who grounded out, popped out, but hits two sharp lines drives right at someone, really did hit the ball well even though his batting average for the game was .000. The hitter (player #2) who dinks and doinks in all four At Bats, who may have beat out one of his "swinging bunts" and one of his ground balls magically threaded the needle between two infielders which neither could get to, looks like he really did well even though he did not hit the ball squarely in any At Bat. Even though the second player hit the ball poorly - he actually hit .500 for the game. So the point may be made that batting average is not a really good indicator of hitting performance if one is using a small statistical base (such as a game's number of At. Bats or a short 75 or 100 At Bat season).

The best evaluator of how a hitter is hitting or has hit, is to evaluate how the ball was hit and not the random result of the batted ball.

It is widely published that NCAA division I studies (and MLB studies) have shown numbers similar to the following:

30% of ground balls result in a "hit" (assign .300 to these)

80% of line drives result in a "hit" (assign .800 to these)

20% of fly balls result in a "hit" (assign .200 to these)

obviously 0% or strike outs result in a "hit" (assign .000 to these)

and you will need to come up with a number for dinks and doinks (including pop ups and "Texas leaguers") I will for the sake of this article use 10% of such result in a "hit" (you can use your own real experience numbers for this). (assign .100 to these).

Using the above percentages I can create a spreadsheet which I call the "Hitting Evaluator and Batting Average Predictor". If I apply the above to the players mentioned in the hypothetical game above, you will see that player #1 would be hitting .500 on my Evaluator (ground out = .300, pop out = .100, and .800 for each line drive - tally these numbers and divide by the four At Bats). Player #2 would be hitting .100 on my Evaluator ( all the "dinks" and "doinks" get .100 - tally these and divide by four At Bats). My premise is that If player #1 continues to hit exactly the way he hit the ball in the game example over the course of 300 or 500 At Bats - he would be hitting .500 since 80% of the line drive would result in a hit etc..... Player #2 would hit .100 using the same principles.

Obviously, the greater the number of At Bats used in the Evaluator the closer it should be to the player's actual batting average. This is why I call it a batting average "predictor" as well as an evaluator. If you plug in 500 actual At Bats into the evaluator - the evaluator average should closely resemble the actual batting average for those 500 At Bats because over the much larger statistical base (500 At Bats) the batting average should have "leveled out" to account for the streaks of "luck" and "bad luck" , good streaks and bad streaks etc...

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