Hey, let’s make up a stat. Everyone’s doing it.

Usually, I advocate a simple approach to following baseball. There are a lot of elaborately constructed stats kicking around the internet these days, but usually the only one you REALLY need is the HBP. You either get plunked a lot or you don’t, and no amount of VORPing or WARing or Runs Created or OPSing or anything else can make up for it if you don’t get hit by any pitches. But I understand the point behind them, when baseball stat fans seem to love trying to roll offense, defense and baserunning into one big stat to compare everyone ever, and account for the context of their park and the season they played in. But they’re all a lot of work and difficult to explain, and usually flawed in the first place because they almost always rely on stats grouped by seasons. But anyway, despite my usual focus on getting hit by pitches I accept that most batters are trying to actually hit the ball when they go up to the plate, and it’s important to measure how well they’ve done that over the course of the season. And it’s not completely unreasonable, usually, to use those past results to build an expectation of how well they’ll hit the ball for the rest of the season.

So, the easiest way to measure a batter’s skill at batting is the batting average. It’s worked pretty well for over 100 years, but being an average, there is a flaw. A batter’s average hits per at-bat is the the same whether he went 4-4 in one game and 0-4 in the next 3, or if he went 1-4 in four straight games. They’re both batting .250, but I’d rather have the guy who’s consistent, and contributed to his team’s offense in 4 games rather than 1. The problem with a season long average, as well as every other season based stat, is that we’ve all witnessed guys who have hot and cold streaks within the year, and since batters are humans rather than box scores (except Arod who was named after his own box score contraction in the 90s), we can guess that some days they feel better than others, and sometimes they have good games and bad ones. Everybody has bad days sometimes, but the question is how often, and how bad.

What I want is a measure of BAtting CONsistency – which I can’t resist calling BACON. Because it has a nice ring to it. And it’s fun to talk about bacon.

Here’s how it works: You take a players batting average and divide it by the players batting average in games in which they have at least 1 hit. Put another way, if you assume there are days when a batter can hit, and days when he can’t hit, we’re dividing his season average by the his batting average on the days when he can hit. Essentially that gives us a measure of how often a player has “off days” where he can’t hit anything, and it effectively weights those bad days by how bad they are. An 0-5 day drags down a players BACON more than an 0-1, that could just be a tough pinch hit appearance or a day when he’s being pitched around with lots of walks or HBPs.

For an example, let’s look at Joe Mauer. He’s played 93 games this season, and he’s had at least one hit in 74 of those games, while putting up an 0-fer in 19. Overall he’s batting .380 for the season, but if you exclude those 19 games where he can’t hit the ball, he’s a batting .471. So we divide the two and his BACON = .807. So he’s pretty consistent – you could say he’s a .471 batter 79.6% of the time, and a guy who can’t hit the other 20.4% of the time. But using BACON factors in the fact that those 19 no-hit games included 69 at-bats.

Now compare Mauer to Ichiro. Ichiro is batting .360 in 110 games and he’s only had 11 games in which he didn’t have a hit. His batting average in the 99 games he contributed a hit to is .392 so his BACON = .918. We already knew he was an amazing hitter, but Ichiro is also the most consistent batter in the league this year, and the only one with over 100 At-bats who is BACONing over .900. So comparing the two, based on the batting average, Mauer is slightly more likely to get a hit in a given at-bat, but I think we can say Ichiro is more likely to get a hit in a given game, and has contributed with his bat to a higher percentage of the games he’s played.

Okay, we probably didn’t need another stat to tell us Mauer and Ichiro are good at hitting. But lets look at another case – Julio Lugo. When Lugo was with Boston this year, he batted a respectable looking .284. However, I think if you polled a group of Red Sox fans, even allowing for the mass-hysteria that usually fills that group, they’d all indicate that Lugo didn’t seem to contribute on the level a .284 average would suggest. In short, he was inconsistent – his game log is littered with 0-4 games with the occasional 5-6, and thus his BACON as of the date of his trade to the Cardinals was just .513. That was 11th worst in the league, making him one of the most inconsistent batters from game to game despite his decent looking .284 average. These guys with the low BACON are going to be the ones that drive you a little crazy as a fan, teasing you with occasional big games between extended cold streaks. After the trade Lugo had a hot streak and his average is up to .309 now, but his BACON is just .640 – the lowest among players batting over .300.

As a basic rule of thumb, if a player has a BACON under .650, he’s not going to be what you’d call consistent or reliable. He’s probably going to be noticeably streaky. Of course, your results may vary.

Here are the top 20 players this year in bringing home the BACON (100 AB minimum):

Batter Total Games Games with
0 hits
Batting Average BACON
Ichiro Suzuki (SEA) 110 11 0.360 0.918
Carlos Beltran (NYM) 62 7 0.336 0.892
Torii Hunter (LAA) 77 15 0.306 0.835
Hanley Ramirez (FLA) 110 23 0.354 0.834
Derek Jeter (NYY) 113 23 0.327 0.832
Scott Rolen (CIN) 91 19 0.313 0.813
Felipe Lopez (MIL) 111 26 0.313 0.810
Joe Mauer (MIN) 93 19 0.380 0.807
Aaron Hill (TOR) 115 25 0.288 0.802
Jason Bartlett (TB) 96 24 0.342 0.801
Tony Gwynn (SD) 78 22 0.278 0.795
Joey Votto (CIN) 87 25 0.318 0.794
Jacoby Ellsbury (BOS) 110 27 0.295 0.794
Carl Crawford (TB) 115 28 0.319 0.793
Ryan Zimmerman (WSH) 114 24 0.302 0.792
Albert Pujols (STL) 118 30 0.325 0.791
Nick Markakis (BAL) 118 28 0.305 0.791
Michael Young (TEX) 114 25 0.319 0.79
Alberto Callaspo (KC) 113 26 0.297 0.784
Marlon Byrd (TEX) 107 27 0.282 0.782

Here are the bottom 20 – none of them are really tricking anyone into thinking they’re doing much good at the plate, with the possible exception of Jeremy Reed:

Batter Total Games Games with
0 hits
Batting Average BACON
Chris Young (ARI) 102 57 0.19 0.517
Edgar Gonzalez (SD) 63 42 0.19 0.516
Ramon Castro (CWS) 43 24 0.234 0.516
Emmanuel Burriss (SF) 59 31 0.238 0.515
Tyler Greene (STL) 36 19 0.219 0.514
Alex Gonzalez (BOS) 70 35 0.207 0.514
Ronny Cedeno (PIT) 72 37 0.196 0.51
Nick Punto (MIN) 85 44 0.21 0.51
Taylor Teagarden (TEX) 38 20 0.198 0.508
Jason Giambi (OAK) 83 44 0.193 0.506
Jordan Schafer (ATL) 50 26 0.204 0.503
Brian Anderson (BOS) 63 36 0.236 0.497
Rich Aurilia (SF) 49 31 0.22 0.495
Ramon Vazquez (PIT) 72 43 0.25 0.493
Greg Dobbs (PHI) 77 53 0.254 0.485
Brian Barden (STL) 47 30 0.233 0.476
Jeremy Reed (NYM) 72 46 0.26 0.463
Jason Michaels (HOU) 69 48 0.224 0.458
Mark Loretta (LAD) 84 59 0.228 0.448
Darin Erstad (HOU) 73 53 0.215 0.439

Just for fun, here are the bottom 5 in BACON among batters with an average over .300:

Batter Total Games Games with
0 hits
Batting Average BACON
Jason Kubel (MIN) 103 35 0.312 0.712
Manny Ramirez (LAD) 66 22 0.31 0.707
Omar Vizquel (TEX) 38 14 0.301 0.707
Delwyn Young (PIT) 87 40 0.309 0.687
Julio Lugo (STL) 56 25 0.309 0.64

Manny Ramirez has always been somewhat streaky, but for him it’s a difference between being really good most of the time to other-worldly during the streaks. Then again, the cynical among you might make a point about steroid cycles here.

Here are the top 10 in BACON among batters under .250 – which should tell you they’re not having great years, but at least they’re being consistent about it. Think of them as the slow and steady types.

Batter Total Games Games with
0 hits
Batting Average BACON
Alfonso Soriano (CHC) 107 30 0.243 0.733
Joe Crede (MIN) 84 30 0.231 0.721
Jimmy Rollins (PHI) 110 34 0.243 0.699
Grady Sizemore (CLE) 91 30 0.242 0.691
Hank Blalock (TEX) 99 35 0.239 0.69
B.J. Upton (TB) 107 37 0.236 0.682
Nick Swisher (NYY) 109 41 0.242 0.682
Kazuo Matsui (HOU) 90 32 0.243 0.677
Brandon Inge (DET) 115 43 0.247 0.676
Ian Kinsler (TEX) 99 34 0.249 0.674

In summary, BACON is a tool for measuring the day-to-day consistency of a batter. It rewards those who contribute at least one hit in each game they play, and punishes 0-for-6 performances more harshly than 0-for-1 games. A batter with a season long hit streak would have a perfect BACON of 1.000.

Thoughts? Criticisms? Suggestions for ways I can explain this better? Let me know.


5 Responses to “BACON”

  1. Anonymous says:

    This is a fun stat, but I'm not sure I can buy into any statistic that defines Jimmy Rollins as a "slow and steady type" he's been more slow then steady.

    Here's the BACON Split (yum) for Jimmy before and after July 2 (like a banana split, but, you know, with bacon:)

    (games/games w no hits/avg/BACON)

    I know it's not fair to pick such an arbitrary date, but I like cherry pick my bacon splits (these puns are completely inevitable, as far as I'm concerned)

  2. pbr says:

    So you're saying his consistency has not been consistent? I should have known this would happen. Now I'll have to create a BACON Derivative to track the changes in BACON over time. Maybe the slow and steady description wasn't great for that group. Maybe it's more like, "they're not good, but at least they show up every game".

    Perhaps I need to compare monthly BACONs and see whose BACON varies the most, or least.

    But, it sounds like my rule of thumb worked pretty well – Prior to early July. Rollins was BACONing below .650, and you felt he was pretty erratic, but he's picked it up for the last month or so and pulled up his season BACON to a more reasonable level.

  3. pbr says:

    Also, I've been thinking about posting about this stat for a couple of years now, but it only really made sense when it became clear that it should be called BACON.

  4. Kenny says:

    I like this stat. It seems to make sense, and I look forward to the day it becomes wildly popular and I will say, yeah, I have a T-shirt from that guy…

  5. LB says:

    Love that BACON. A buddy on my blog dropped this link, great stuff. I’m adding you. Not that it matters, I get a crappy 200 visits a day but there it is.

    I’m surprised FanLaughs hasn’t picked up on this and starting some kind of “beef” with you.

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