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SABR42 Day One: Afternoon Presentations & Knuckleball movie

SABR42 Day One: Afternoon

I saw three research presentations (out of four possible) this afternoon, and then went to meet up with my fellow panelists for the Women in Baseball panel, which I had the honor of speaking on. I can’t really blog that one since I was on it and couldn’t take notes! So someone else will have to write up what that was all about, haha.

This afternoon I saw:
Vince Gennaro: Value Strategies for Building A Roster
William Spaniel: The Fear of Injury, Explaining the Delay in Contract Extensions
David W. Smith: Shutting Down the Running Game by Limiting Steal Attempts

Here are detailed descriptions on each:

Vince Gennaro: Value Strategies for Building A Roster

Vince Gennaro led off the afternoon research presentations with a discussion of not one but FIVE areas that teams could be investigating in order to maximize value, reprising some of what he talked about at the SABR Analytics Conference. Five areas aimed at paying the right amount for players or the needed talent. “There’s never a silver bullet answer to this stuff,” he said, so you have to look at lots of little pieces of information to put it all together. Vince is one of the sharper analytical minds I’ve had the pleasure to work with (he wrote numerous articles for the Yankees Annual, and he’s now the president of SABR and I’m the publications director).

Value=Acquiring expected wins at “below market” price
Value = $/WAR

The five elements being considered:
1. quality of opposition
2. platoon players inefficiently priced
3. translation from regular to postseason
4. optimizing timing of transaction (value is affected by the calendar)
5. buying risk at the right price (MLB teams do a poor job valuing risk)

1. Playing against tough opponents
The unbalanced schedule creates tremendous inequities in who a batter faces and who a pitcher faces. So player stats are not apples to apples. Park effects have been around for a long time and are well accepted when it comes to evaluating a player’s numbers. But there is no stat for measuring and adjusting for the opposition. We’re working on it: I try to partner with others with more math sophistication than me to calculate this.

CJ Wilson vs Ricky Romero
In 34 starts CJ Wilson had 14 starts against the bottom third of teams vs Romero pitched in the tough AL east. Their ERAs were nearly identical 2.94, 2.92, but if you impute the imbalance, it was more like 3.12 versus 2.74 — that would be a much bigger swing. Nearly forty points. At least one team I spoke to in the national league did this adjustment on pitchers to acquire. They took a reliever from the AL east who didn’t seem that great (and so isn’t being paid that much) and now he’s doing much better.

2. Exploiting the platoon advantage
Gaining a platoon advantage is cheaper than buying “quality.” Buy a half a player instead of a whole player, or 3/4 of a player if they’re lefty. (Shows a graph demonstrating the advantage in lefty platoon at bats.)

Look at Andre Ethier last year and the previous seasons (this season not totaled yet). His splits weren’t good. Struggled against lefties. I had him valued at $13 million in my free agent model. (This year he’s done much better and got $17 million. But never mind about that.) Go look at Andruw Jones and David DeJesus as a platoon. Jones .842 3 year OPS vs LHP, and DeJesus .824 vs RHP. Can buy both of them at 60% or less of the price for the star. Jones might’ve gotten $3 million and DeJesus $5 million. There are ways to go cheap in terms of value. Can’t do it all the time since you only have 25 roster slots, of course.

3. Transferring Regular Season to October
What if we had a way to tell what a player was going to do in the postseason? Wouldn’t that be a Holy Grail? How can we do that? Here’s one thought.
-measure how hitters play against various quality levels of pitching
-measure quality level of postseason pitchers
-translate that into a postseason expectation

Divided all pitchers into 5 quality levels, with OPS against (LL, LR, RR, RL) using 3 years worth of data. All matchups look similar.

Ethier feasts on weak LHP but is stymied by top LHP.
A thousand PA in the Ehtier db, and it shows he really struggles against top pitching.

Pablo Sandoval : crushes top LHP and is league average against weak RHP.

In the postseason, top 20% of the pitchers get 37% of the postseason innings, and then next 20% get 28% — and this is only starters. (Relievers are expected to be even more skewed.)

Every hitter should see degradation of their numbers in the postseason. Jeter sees less degradation than most, whereas A-Rod sees much more because the guys he really feasts on aren’t getting many postseason innings.

4. Optimizing Timing of Deadline Trades
-optimal timing creates the most value

For the seller, the price is affected by the competitiveness of teams, how many are buying and selling, etc.

When do you know you’re in contention? (Shows graph of the “uncertainty of contention”)

You learn a lot between June 26 and July 10, but the learning levels off around 8% at July 10.
(The next graph shows a starting pitcher example: as every 5th day their value decreases since you lose the amount of starts you could have for him.) If you wait too long after July 10th, you lose the values of players by waiting any longer than that.

It’ll be really interesting to see if the second wild card will change this dynamic. This was based on the last 5 years of data.

5. Buy a Lottery Ticket
Understand your risk preference.
Is a point estimate of expected performance enough to value a player? What’s the point range distribution around that expectation?

Look at Willie Bloomquist, delivers about half a win year after year after year. That’s all you need to know, low standard deviation.

But when expected performance and POSSIBLE performance are far apart, you might be smarter to value a player based on the tail instead of the core expected. Look at Manny Ramirez.
High standard deviation for performance, bounded downside on the managers choice to play him or not, and non normal distribution. There’s a non-zero chance he could put up a 5 win season. Maybe it’s a 7 % chance. So should you value him as a 5-win player or a 2 win player which is more likely? How about injury prone players?

So there you have it. Five possible different measurements and evaluations that teams could be doing regarding value. You can find more of Vince’s thoughts at


William Spaniel: The Fear of Injury, Explaining the Delay in Contract Extensions

William Spaniel published a game theory piece recently in the Baseball Research Journal and is the author of the book Game Theory 101, so I was expecting a game theory presentation. And that’s indeed what it was. He also put up a QR code that would lead to the full paper of his presentation.

Spaniel got started on this topic when Jared Weaver signed his contract extension with the Angels for $85 million. How would he have done on the free agent market, though? He would have made a lot more. Santana got 6 years $137 million, Cliff Lee for $120 million 5 years, etc.
So the puzzle is Why didn’t Weaver go to free agency when he would have made more money?
Weaver said “how much more money do you need?” But is that what motivated him to sign the extension with the Angels?

More likely it was risk aversion.

Risk aversion:
-playing games risks catastrophic injury
-would you prefer $85 million guaranteed or $100 million with a 10% chance you might get zero?

Risk averse individuals would definitely find it worth it to take the guaranteed lower amount.
How does risk aversion impact contract extension negotiations?
Why do some pursue free agency while some sign extensions when they do?

We have a strategic situation, contract negotiations.
Game theory will sort out the logic. (Spaniel then lays out formulas for the situation, defining variables, etc. I can’t come close to recreating the formulas or explaining how game theory works, so I will suggest you have a look at the whole paper on his website:

General conclusions:
Results only require the team to be less risk averse than the player.
With a fraidy cat player, offer the smallest amount you can.

1. Teams will always resign a player if he is sufficiently risk averse.
2. Delay in agreement is a result of the team’s uncertainty of how risk averse the player is.
3. Negotiations should not be suspended in-season. Teams lose the chance to learn how risk averse the player is.
4. Perfect player safety is suboptimal for the team in contract extension negotiations.

* * * *

David W. Smith: Shutting Down the Running Game by Limiting Steal Attempts

I think I have seen every one of David Smith’s presentations at SABR conventions dating back to 2003. which would make this my tenth one in a row. Smith often operates on what I feel is the classic “SABR” model, which is to take some truism in baseball, the sort of thing TV broadcasters say, and then think, wait, is that really true? And thanks to the huge dataset known as Retrosheet, which Smith himself has shepherded so ably all these years, he can actually answer the question most of the time. Past presentations have examined such statements as “good teams win close games.” (Answer: yes they do, but they also win ALL kinds of games, and in fact a better predictor of how “good” a team is isn’t how many one-run games they win, but how many blowouts they win.)

This year David took a look at steal attempts. It’s interesting because the steal is one of the only official categories that records willful action on the part of a player. Steals and sac bunts are intentional. We focus most on the success rates. They say if you steal successfully twice as often as you are caught, you’re doing OK and 2:1 is a useful, easy ratio.

How often do steals happen? There’s a huge variation. American League in 1950 the value is so low teams were stealing only one base per five games. Whereas up on the high end are some almost a base per game per team. From 1980 through 1992 all of a sudden the NL is 20% higher than the AL, and then in 1992 the difference went away and the two leagues are fairly close again. (No idea why.)

Second base is stolen 88.2% of the time, 3rd 10.9 %, and home is under 1%.

Percent success on steals of second has been on steady increase. Runners are caught less often now and in the last 15 years it’s been a net positive for a team to steal, whereas before this, it wasn’t! Not exactly what most people would think.

In over 9 million plate appearances, over 3 million of them had a runner on first base. Concentrated just on ones where there was ONLY a runner on first. (Showed several tables of pitchers and then catchers showing the rate at which people ATTEMPTED to steal and then their success rate.) Some fun numbers from those:

Jim Kaat only allowed people to steal 4.8% of the time and they only made it 58% of the time.
Nolan Ryan, though, allowed them to try 19% of the time and they were successful 73% of the time.

Yogi Berra, they only ran against him 4.9% of the time and only 46.9% of the time successful.
Craig Biggio back when he was a catcher, 14.3% ran against him… which is why he was converted to second base.

Roy Campanella threw out 23 consecutive base stealers and it took two years because people didn’t try to steal against him.

Then came the Women in Baseball panel, as I said, then the Women in Baseball committee meeting. The committee is starting work on a book about the Colorado Silver Bullets.

I capped off the day with the screening of the film KNUCKLEBALL! This documentary film follows Tim Wakefield and R.A. Dickey through the 2011 season and it was PHENOMENAL. A terrific documentary, great music, the visuals were completely stunning. I don’t even know how they had footage of half the stuff they had historically, but they did, and even though (or perhaps because of?) we were watching it from a laptop computer being projected with a conference projector, all the colors were quite rich. I’m sure every frame of this sort of thing is digital graded nowadays, but it was very visually engrossing as well as being a terrific topic. It’s only been shown once before and I guess we don’t know where it might be shown next, or if it will do the film festival circuit or what? Or if it will just end up going straight to MLBAM outlets? I don’t know, but if you get a chance to see it on the big screen, do not pass it up.

And now it is time for me to pass out. The first thing tomorrow is Terry Ryan’s speech (GM of the Twins) and I don’t want to miss that, but I’m so wiped out from today that I might sleep through him. Otherwise I won’t make it through the ballgame tomorrow.

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