Project Context Neutral Runs and RBIs

Projecting a players Runs and RBI’s is a pain, and it’s largely considered contextual. So if you’ve got some good hitters hitting in front of you, you’re going to get more RBI opportunities, or good players hitting behind you, more Run opportunities.

The problem with this, is that context changes often. A team that previously stunk, may have a guy or two breaking out, and now suddenly another player is thrust into a situation where he can generate more runs. A key guy might get injured, traded, or simply moved around in the lineup.

For this reason, I’ve been working on a way to project a guys runs and rbi’s based on his skills alone. I’ve tweaked my process a bit over the years, and here’s what I’ve found the best method:

xRuns = HR + -.218 + .191 * (BB - .333 * CS) + .273 * (HBP + 1B - .666 CS) + .363 * 2B + 1.366 * 3B + .505 * SB

So just to summarize what this means, Extra base hits generate more runs, with triples generating bonus runs (because they indicate a speedy player, who’s going to score on more Singles then other guys), and net stolen base gains also improve your chance to score runs.

xRBIs = 2 * HR + .640 + .004 * (BB + HBP) + .234 * 1B + .427 * (2B + 3B)

With this one, again we see hits generate RBI’s, with extra bases generating more. Home runs generate bonus runs because you’re knocking yourself in, as well as anyone on base, and home run hitters generate more Sacrifice Flies.

Let’s look at some sample results from my 2012 projections:

name xRuns xRBI
Kemp 109 108
Ellsbury 103 97
Bautista 100 113
Bautista 100 113
Kemp 109 108
P Sandoval 89 105

Ellsbury is an interesting one on this list, Sitting in the #1 hole he traditionally had very few RBI’s historically, this system picked him for an RBI increase last year based on his budding power (and his lineup position changed to fit his new skillset).

Sandoval is also an interesting inclusion, he’s had budding HR and 2B power, and a change in his context could put him in line for a lot of RBI’s.

Obviously this method is not perfect, context does exist, I just find that it’s so fluid throughout the year, it’s fun to just ignore it, and project based on a batters skills. I find this particularly satisfying in fantasy baseball, because it’s a fun way to identify breakout players. A player with budding power (ellsbury, granderson), will eventually have their lineup position improved to take advantage of that power. These are two guys who I specifically drafted last year based on my projections, who both had their context improve, to match their skills.

Predicting Runs and OBP

OK, so we've talked about Batting Average, now it's time to move on to OBP, and Runs. OBP is a measure of a hitter's ability to get on base, while runs measures the number of times he's crossed the plate. OBP is a product of a batters batting average, combined with his ability to take walks. Runs, is a product of a runners ability to get on base, run the bases, and ultimately get some help from his teammates.

First, how do we project On Base Percentage. Just like batting average, this will fluctuate a lot from year to year, based on a hitters luck with balls in play (BABIP). Since we've already determined batting average, the main thing to look at now, is a players walk percentage. Unlike batting average, this is more about the players skills, and thus, it's easier to predict. This is a stat that players tend to improve on as they develop, so it's easier to expect a player to repeat, or even improve upon last years walk% (and thus improve their OBP). If a player's walk% remains relatively constant over their career, I'll use that walk%. If they have shown improvements in recent years, I'll tend towards those numbers. Rarely does a player actually decline their walk% (though it does happen). Unfortunately, built into OBP is a player's sacrifice fly's, and bunt's. This makes it impossible to simply project a players OBP using their batting average, and BB% alone (Sac fly's, and bunt's will vary a lot from player to player, and even from year to year). So the way that I project it, is to pick a year in the players career that best represents the walk % I predict for that given player (if it exists), and I'll add or subtract from that years OBP based on the batting average I projected for them. So if their batting average was 20 points better in my projection, I'll add 20 points to that particular OBP, and use that as my projection. For younger players, this is more difficult, and I find myself often just taking an existing OBP (career, or even 1 year), and tweaking it upwards. For young players, I will look at their minor league numbers as well, for a point of reference, as they tend to move close to (and sometimes exceed) their minor league numbers as time goes on.

Alright, so there's OBP, my method's aren't highly mathematical, but I think taking into account trends in BB%, and taking out the batting average fluctuations, makes for a fairly accurate OBP projection. Now it's on to predicting a players runs, and this is where my research gets a little more interesting. Runs are based on a few things, some of those things (OBP, Speed, Plate Appearances), are statistical in nature, while others (where they hit in the lineup, and how well the people behind them in the lineup are knocking them in) are out of the players control, and difficult to project. So what I've done, is thrown out what's out of the players control, and figured out a way to predict a players runs, based on their skills alone. So what you get is "skill runs", that is, the number of runs that a players skills should allow him to score. In a better batting slot, they will perform better then their skill runs, while in a worse one, they will perform under it. But batting slot is very difficult to predict, so for the sake of our projections, let's throw that out entirely.

So how did I do it? I Took a large sample of data (3 years worth of player data, that I took from fangraphs), and I ran some statistical analysis of a players runs scored as compared to their Stolen bases, OBP, and PA. When I did this analysis, I came up with the following equation to predict a players "skill runs": -90.241129 + (Plate Appearances x -90.241129) + (OBP x 200.8088179) + ( SB x 0.293131537 )

Using this equation, and my projections, here's a sample of what I came up with, for the leaders in runs scored next year in 2010, and I'm pretty happy with the results:

Player	Skill Runs
Pujols	115
Ellsbury	111
Reyes	109
Figgins	108
Abreu	107

Now obviously there is a good chance that team factors will push these guys, and others, up and down in the list, but given skills alone, this is where I project them to be. Note: I have everyone set t0 700 Plate Appearances currently, so that also skews the results, more accurate PA projections will change this.

At the bottom end of the spectrum, is Benjie Molina with 80 Runs. Remember, that's with him projected to have 700 plate appearances, which he's not going to do, nor has he done at any point in his career. Interestingly, there is not a huge difference in runs scored between the top, and bottom players, this just shows that by a large margin, plate appearances are the biggest factor in a players ability to score runs (which makes sense).