**Do Batters Make Slumps Worse by Trying to Escape Them?**

Jeff Switchenko, with several co-authors

**Hitting with RISP: Real differences between players**

by Eric Van

**Are Outs Made on the Bases More Harmful than Other Types of Outs?**

David W. Smith

**Do Batters Make Slumps Worse by Trying to Escape Them?**

Jeff Switchenko, with several co-authors

Possible causes of slumps:

-lack of concentration or attention

-injury

-extended stretch of good pitching

-luck

etc

What players do to get out of slumps

-sacrifice chickens (a la the movie *Major League*)

-change underwear

-get a new batting coach

-get a new psychologist

etc

This study sought to characterize slumps with respect to observed versus expected frequencies.

length – number of AB over which it happens

severity –

Retrosheet all at bats from 1999 through 2009 collected.

Observed slump proportion is proportion of ABs that a player has a rolling average at or below the specified severity/length

Expected .266

a player’s hitting performance completely random around the average BA .266

assume all at bats are independent trials

Percent of players with slumps of .200, .100, and .000 by year (minimum 20 ABs)

Percent of all rolling averages of 20 ABs below .200 and .100 by year (observed vs expected)

percent of time spent in slumps of .200, .100, .000 over various length of ABs

Almost all players experience at least one .200 slump

35.9% of all rolling averages for .200 slump, 8.3% for a .100 slump

Expected 35.2 % for .200 slump, 6.8% for .100 slump

In other words, players are spending MORE time in slumps than you would think they would by random.

Shows some graphs that show the amount of time spent in slumps is greater than the time expected, and that the longer the slump is, the GREATER the amount of time spent in it beyond expected.

Now same graph showing mediocre players and there is not s much a discrepancy between observed versus expected. Mediocre come out about the same, while the worse players have a big discrepancy!

The overall effect we see is driven by the weaker players.

Changing strategy is “worse” than just riding it out for probability to bring it around again.

Players in bad slumps, if they are weak players, may have ‘censored’ data since then they are then benched.

**Hitting with RISP: Real differences between players**

Eric Van

Three years ago, Eric was reading a Cubs blog, that was assuring readers that Alfonso Soriano’s inability to hit with RISP was not a problem, because there was no predictive value in those numbers. But Eric didn’t buy his argument. Because Eric had actually seen Alfonso Soriano hit. Soriano thought his job was to drive runners in and not to walk. When he came up with runners on, he would be trying so hard to hit the ball, he would expand the strike zone and swing at bad pitches.

Each at bat has a unique pitcher-hitter dynamic. The pitcher is constantly changing his approach to try to take advantage of the base-out situation, and likewise the batter. There is no way that all batters have the same ability to take advantage and change approach to all other batters. Some have sub-optimal approach.

Some real work on clutch hitting has been done by Tom Tango and Baseball Prospectus, but neither asks the questions to separate RISP from close and late.

Looking at career total adds noise because what about batters who figured out how to change their approach? That is averaged out and made invisible.

If we can no longer correlate year to year, what can we look at?

If RISP hitting differences are real, then hitting with runners in scoring position is actual 6 different things. It’s hitting with a runner on each base, or two men on, or men on the corners, etc…

In the “pure” approach, we would say that all 6 of these situations would NOT correlate to each other, whereas if RISP hitting is *real*, we will see differences between these situations and bases empty.

Study used retrosheet data from 1980 to 2009, all players whose careers began after 1981.

Using weighted OBA, a form of Linear Weights per PA, as outlined by Tom Tango in Fangraphs

Evaluating four rates in all of 24 base/out situations:

K% strikeouts

W% walks

HR/C

BABIP

Bases loaded is not as unique as people think. Bases loaded and men on first and second is very similar.

What is the baseline? Should bases loaded be compared to bases empty, or with man on first?

Van then demonstrates a very strong correlation between base out situations. I can’t recreate the math but he shows how using year to year correlations just won’t reveal these kinds of correlations.

How many players are going to be actually better at this skill?

By definition of average, any given player has a 50% chance of being better or worse than the average in each situation. How many would you expect to be better or worse at all six situations?

It turns out 21 more players than expected in this nearly 500 player sample show up as better or worse than predicted. Or one player in 23 is going to have real better or worse hitting skill with RISP.

If we postulate two sub-skills, one with the ability to adjust to being pitched around when there is first base open, versus the ability to hit when base occupied, it shows more significant splits than expected.

It seems obvious that coaches and managers KNOW that guys have these skills, but we have been bedeviled by the inability to demonstrate it mathematically. NOW you can go home knowing for sure that RISP skills are real and when we go to the game tonight and a guy comes up with men on, and we know he has good career numbers, we’ll be the first fans to be able to say “Hey, that’s not random.”

(**EDIT:** Eric tells me later that the details of this will be explored in a future article for* The Hardball Times*. So all the math and graphs I couldn’t recreate here you will be able to read there in greater depth and detail.)

**Are Outs Made on the Bases More Harmful than Other Types of Outs?**

David W. Smith

David Smith, the driving force behind Retrosheet, gives a talk every year that is not to be missed. His usual *modus operandi* is to take the type of thing that Tim McCarver says on game broadcasts, the kind of “truism” that gets repeated a lot in baseball, and try to debunk or disprove it. (Or even prove it.)

“As you know, McCarver often says if the leadoff batter walks rather than getting on by some other means he is more likely to score. It is demonstrably untrue.” In fact, Dave himself demonstrated it at a previous SABR convention. Likewise they often say that pitchers running the bases hurts their performance afterward. Also proven untrue by our own Mr. Smith.

So, are outs made on the bases more harmful than other types of outs? Is there some kind of psychological deleterious affect of these outs? Or what?

Start by looking at the game state and runs scored. What is the chance of scoring before the runner has this action, versus what is the chance of scoring after? There are now over 10 million plays in the Retrosheet database, 109 seasons, and over 139,000 games (over 80% of the total of all major league games). This study will use them ALL.

David then shows some charts demonstrating the likelihood of scoring in various men on base situations.

You can’t assume that going from “no out, no one on,” to “one out and a runner on first” that the two ways to get to that situation are the same. Markov transition assumes it doesn’t matter, but let’s not assume. Looking at the possible ways, runner first, then the out, versus the other way etc…

Well, for this transition it turns out NOT TO MATTER how you got there. Appears path independent.

Type of out? .52 for a ground ball or fly ball, and .50 in strikeout. Is that .2 difference significance? 1% of the time. Strikeout might demonstrate slightly greater pitcher control in those situations. Hit by pitch shows .56 but we don’t have a lot of HBP data.

Overall if this transition is .52, and we split it into the home versus road team, we find it gives the home team a .54 advantage, and the visitors .50.

Looking at ALL transitions where an out is going to be added, fifteen situations, well, there is about a 1% chance that a strikeout will reduce the scoring.

The team that is making the more baserunning outs should lose more of the time, yeah? No. It shows they tend to win more often. Because they have more men on!

Now it’s really low outs on the bases overall compared to before.

Averaged by team shows random.

Players and coaches have optimized risk already. Manner of the out is not important.

It would have to be NO. Outs made on the bases are *not* more harmful than other outs.

*(Did you enjoy reading this blog entry? Please consider buying me a hot dog.)*

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