Mandatory Credit: Jake Roth-US PRESSWIRE

Who was the Braves most consistent hitter in 2011?


Right now I am in the middle of a statistics class and we recently went over standard deviation. For those of you who don’t know what standard deviation us I will bring in Wikipedia.

Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or “dispersion” exists from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values.

What I am doing is pretty much, “who’s batting average fluctuated the most over the entire season?”

For Brian McCann I will show you how the math is done for the stat junkies out there who care:

the rest after the break…

We need to the average for each month. McCann’s were .301, .304, .342, .275, .146, and .200. Then we have to use the formula* (x1- season average)2 + (x2- season average)2 … and so on until we have used each individual average. X represents the monthly average. After we add them up we will take the square root of the number to find the standard deviation, and find out who really was the most ‘consistent’.

*you can also do all of this with a graphing calculator…

McCann’s standard deviation came out to be .0736. The higher the number the less consistent the batter. Now we will repeat for the rest of the team.

McCann- .0736

Freeman- .0542

Uggla- .0704

Gonzalez- .0727

Jones- .0470

Prado- .0347

Bourn (including time with Astros)- .0338

Heyward- .0636

Apparently in 2011 Michael Bourn was the Braves most consistent hitter. Don’t read into this too much however because I only used the averages each month instead weekly which would work much better. Also, missing time (McCann, Prado) can really skew the data. It’s not an exact measurement when you use it the way I did, but it seems to be at least reasonable. I mean, Michael Bourn was the leagues least volatile hitter at one point last season.

Take it with a grain of salt. This was more of just a curiosity piece but I am not surprised at all that Michael Bourn, Chipper Jones, and Freddie Freeman were the most consistent hitters on the team. Are you?

Tags: Atlanta Braves Chipper Jones Freddie Freeman Michael Bourn Most Consistent Hitter

  • leetro

    I know BA is the standard, but using OPS or wOBA would be better. I wouldn’t say a month of .300/.350/.400 is the same as .300/.400/.500. Just a stat geek putting in his two cents…

  • http://tomahawktake.com/ CarlosCollazo

    @leetro Definitely agree with you.

  • http://www.sabbump.org/ clearwall

    My first guess was going to be Freeman, and of the players who didn’t have debilitating injuries, he’s the guy. You’re right that missing time really will skew that number, not just because of less ABs to lower the final average, but in cases like Prado, you may have a whole less month of data to use. Also, I dont think Bourne should even qualify. I dont consider him a “Braves hitter” last year.

  • Shan0806

    I understand what you tried to do here, but there is a major problem with the way in which you employed the data, specifically the mean (or 2011 BA) for each individual hitter. By taking the average of the monthly averages, you misrepresented each batter’s actual average for the entire season. Since each month one should expect a batter to have a different number of ABs (the denominator, in this case), one must not take the average of the monthly averages, as this will give you an erroneous number for BA over the entire season.

    Take, for example, Brian McCann. By averaging his monthly BAs, one would conclude that his BA over the course of the season was .261, when it was in fact .270 (126/466). The difference can be accounted for by recognizing that the number of ABs (once again, the denominator) he received on a monthly basis was different, meaning some months are weighted more heavily than others in the final product. The difference is not going to be huge when looking at players with relatively stable AB baselines from month-to-month (Freeman and Bourn, for example), but the STDEV on the whole should assuredly change when this error is fixed.

    On another note, I’m not wholly convinced that being consistent is in and of itself ‘better’ than being inconsistent. If Batter A hits .300/.400/.500 in his first 250 PAs and .300/.400/.500 in his next 250 PAs, while Batter B hits .200/.300/.400 in his first 250 PAs and .400/.500/.600 in his next 250 PAs, should Player A be lauded because he was consistent? By that same token, should we take away from Batter B’s season because he was relatively inconsistent? I know this was not at all your implication, Carlos, but it is something to ponder.

  • http://www.sabbump.org/ clearwall

    @Shan0806 Im not a statistician, so I couldn’t eloquate it as well as you did, but that was exactly my issue too. Taking each month’s BA is the wrong approach.

  • http://tomahawktake.com/ CarlosCollazo

    @Trey Peters@Shan0806 Great points, and I thought of that last point about consistency while I was in the middle of writing. Consistency itself should not be an accomplishment. Consistency at a good level should be. The way I did this is not extremely accurate and we should go ahead and take McCann and Prado out of the equation (one of Prado’s months he had a .300 BA in around 20 plate appearances) but I feel I feel like it did succeed in telling me what I wanted. That is, Freeman, Chipper and Bourn were more consistent than Uggla.

    I am glad you guys have taken an interest in this and thanks for your feedback. I might have to do an in depth ‘consistency piece’ at some point to have something more accurate.

  • Shan0806

    @CarlosCollazo You are drawing conclusions from incorrect results, which are the result of an incorrect process. Until you test your hypothesis in a correct manner, you can’t draw reliable conclusions. If you choose to do so, that’s referred to as confirmation bias.

  • http://tomahawktake.com/ CarlosCollazo

    @Shan0806 Agreed.