Baseball is unlike many other sports in that players can be so inconsistent [1]. Instead of being an actual phenomenon, maybe that mostly owes to the wealth of sabermetrics where inconsistencies can be proven easier. Many hitters face slumps or just general inconsistencies across seasons. Even among players applauded for their consistency there is much variance. Here, I focus on Chipper Jones, exploring his consistencies in batting average.

Chipper Jones is an 8x All Star Hall of Famer, considered one of the greats in Atlanta Braves history [2]. With many praising him for his consistency I take a look at how his numbers stack up to others. In comparing him to Tony Gwynn, considered one of the greatest hitters of his time, and Kurt Suzuki, an all-round average player, we see some interesting trends.

I took each player’s yearly batting average and found their standard deviation from their career batting average. All three players have a relatively high standard deviation from their career BA, so they regularly deviate from their career batting average quite a bit. A near perfect player (Superman for short) with season batting averages +/- 1% away from his career BA would have a deviation of∼0.00093. This illustrates just how inconsistent baseball players are. This is not to say one expects a superman to arrive, such perfection is impossible.

This chart does well to show inconsistency, but what is the negative consequence of such inconsistency? Might a team prefer a player that has a stellar year, followed by an inadequate year? Maybe some would, a team with depth could handle a player’s slump and equally benefit hugely from their red-hot season. With that being said, I think it’s safe to say the lower a player’s standard deviation in BA, the better, more complete a player he is.

So this proves baseball players are inconsistent. Yet, the actual variance between players’ standard deviation is not very statistically significant. It does to an extent show Chipper as the least consistent, but more so just reinforces the notion of all baseball players as inconsistent.

Jones went through his worst slump in 2004, which broke his six-year streak of <.300 batting average, ending with .244. Chipper stated his lack of consistent playing time as the major factor, with a hamstring injury seeing him in and out of games, throwing his groove out of whack.

Hitting comes with repetition…I couldn’t get enough at-bats to go out there and do things consistently. When I did come back, I felt like I was going through spring training all over again. My bat speed was slow. I was behind everything – Chipper Jones, reflecting on his ’04 Season in September ’04 [3].

Nate Silver has disproved most notions of streaks in sports [1], however here Jones cites a concrete reason for his decline – inconsistent game time and injury – instead of a vague notion of streaks.

In this scenario I would agree with Chipper, he played the least amount of games in the 2004 season than seasons past. Post-2004, Chipper’s game time and hits continued to go through dramatic ups and downs. In still struggling to cope with injuries impacting his game time, his offensive numbers lacked consistency across seasons.

We can see as Chipper’s game time decreased, so did his batting average, in general. In ’05 and ’06, his BA actually increased while his game time decreased. Whether this is regression to the mean or just Chipper getting better at responding to interruptions in game time cannot be inferred from the data alone. Despite that, Chipper Jones’ inconsistency seems to be best explained by lack of continuous game time [2].

With a lot of mystery surrounding players’ inconsistency and many sports psychologists trying to understand it, here we have a more cut and dry reason. There are infinite possibilities to explain consistency, new hitting coaches hired, a move to a different team or a personal problem to name a few. These can all have effects and can affect some players more than others. This article does little to explain other factors and could benefit by exploring other variables that may have contributed to Chipper’s variance in offensive stats. With that being said, with a strong correlation such as this, it can be said with reasonable accuracy game time was a strong factor in his batting average.

The plots grouped in the upper middle of the graph are 8 of his first 9 consecutive playing seasons, they gave him his most consistent run of games, which in turn he produced his most consistent batting averages. One can see clearly after these 9 years his batting average is sporadic. The r² value of 0.078 does little to support a notion of batting average increasing as plate appearances increase. This is more a fault of the graph than the data – in taking each year as a standalone data set, this has allowed for outliers (unusually poor/great seasons) to sway the trend line.

In line with this, the graph below has softened the impact of outliers, while still including the outliers in analysis (to lessen selection bias on my part). It softens the impact by grouping BA across seasons into quarters – E.G. In ’06 Chipper played only 110 games with a BA of .324, this is an outlier, but by grouping it this means this one high number won’t distort the overall trend too much. I sorted the data by games played each season and grouped them into quarters (1st quarter – all seasons with 95-126 games played, 4th 157-160 games played) [3]. I plotted the batting average of each quarter to find a relationship between games played and batting average.

This trend line with a high r² value shows batting average increasing as game time increases. Chipper is a player that generally needs regular game time to produce some good offensive numbers.

In sum, Chipper Jones suits such analysis as this, in that one can deduce reasons for his variance quite well through trends in data. Instead of coming up with tricky theory to explain such variance, credibility is given to an evidence-based conclusion like this. Chipper was an excellent player for the Braves and was rightly inducted into the HOF as soon as he was eligible.

Bibliography

[1] M. Lopez, “Exploring Consistency in Professional Sports: How the NFL’s Parity is Somewhat of a Hoax,” [Online]. Available: http://www.sloansportsconference.com/mit_news/exploring-consistency-in-professional-sports-how-the-nfls-parity-is-somewhat-of-a-hoax/. [Accessed 11 February 2018]. [2] Fox Sports South, “Braves legend Chipper Jones punches Hall of Fame ticket in landslide,” 25 January 2018. [Online]. Available: https://www.foxsports.com/south/story/chipper-jones-hall-of-fame-atlanta-braves-012418. [Accessed 10 February 2018]. [3] New York Times, “Chipper Jones and the Braves Are Hits Again,” 19 September 2004. [Online]. Available: http://www.nytimes.com/2004/09/19/sports/baseball/chipper-jones-and-the-braves-are-hits-again.html. [Accessed 10 02 2018].

All other data on players taken from baseball-reference.com

[1] Nate Silver explored streaks in sports in reference to Basketball in The Signal and the Noise. Writers, commentators and players alike cite streaks as a real thing, that when players are ‘hot’ they are more likely to keep the streak going. While there may be some truth to this, I think this thought mostly comes from confirmation or selection bias. A player goes through a lucky streak but it may not be an indicator of future performance; when the inevitable decline comes, it is simply regression to the mean.

[2] This could be correlation, not causation, one wonders whether the lack of game time is because of his poor form (not to count for injuries), not the other way around. Most likely, it is some sort of combination of both. For the most part, Chipper was played whenever he could; it was just as he got older he struggled with injury.

[3] The quarters are weighted, in that the first quarter encompasses all seasons where Chipper played 95 – 126 games and the fourth 157 – 160. The quarters factor in the amount of seasons under each quarter, not just simply (160-95)/4 or 160/4 = 4 quarters.