Umps make calls based on race?

[Electron Blue]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

[Rob]

1%??? Those dirty racists. Get em outta here.

[Cynosure]

Sorry but that doesn't seem like a big enough factor nor does this study seem legit IMO.

[cubfan]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

 

I would find it hard to believe that the error in such a study would be less than 2 or 3% let alone less than 1%

[Post Count Padder]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

 

I would find it hard to believe that the error in such a study would be less than 2 or 3% let alone less than 1%

As a statistics student for 2 years, I believe that the margin of error is usually around 3% (based on sample size of the population).

 

A 1% differential? You gotta be kidding me. How is that significant?

[Cynosure]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

 

I would find it hard to believe that the error in such a study would be less than 2 or 3% let alone less than 1%

As a statistics student for 2 years, I believe that the margin of error is usually around 3% (based on sample size of the population).

 

A 1% differential? You gotta be kidding me. How is that significant?

 

It's not, the guy just needed a story.

[B]

That explains why the A's get all the calls.

[Omar]

Get Al Sharpton & Jesse Jackson in here!

[OleMissCub]

http://www.gifflix.com/data/media/15/racista1xj0ce7yc.gif

[cbbryan]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

 

Was I the only one that thought Gary Sheffield was going to be part of this thread?

[Alfonso Soriano]

No wonder we got swept by the Astros

[Derwood]

1%= 1 out of 100. There are usually, what, about 250 pitches combined between the two teams in a standard game? So 2-3 pitches per game are being called based on race?

[CuseCubFan69]

Those who race to first before the ball gets there after they hit a grounder are usually safe and those who don't beat the ball there are usually not. I think they just don't like slow guys. I'm pretty sure the umps are wrong 1% of the time too.

[Skyballer]

http://www.gifflix.com/data/media/15/racista1xj0ce7yc.gif

:lmao:

[jyoung55]

MSNBC.com

 

A new study by a professor at the University of Texas at Austin suggests that home plate umpires call balls and strikes more favorably when the pitcher is their same race, Time magazine reported.

 

The research team led Daniel Hamermesh, professor of economics, found that umpires call strikes more for pitchers of their race and balls more when the pitcher is of another race, Time said.

 

The study found that the disparity occurred in 1 percent of pitches.

 

am I undersyanding that right? it sounds like it isn't a big deal, like it could even be random.

 

even if true, it would pretty much fall in line with similar studies.

 

I would find it hard to believe that the error in such a study would be less than 2 or 3% let alone less than 1%

As a statistics student for 2 years, I believe that the margin of error is usually around 3% (based on sample size of the population).

 

A 1% differential? You gotta be kidding me. How is that significant?

 

It's not, the guy just needed a story.

 

Someone should MSNBC a refresher in stats, so they don't print this garbage.

[RynoRules]

1%= 1 out of 100. There are usually, what, about 250 pitches combined between the two teams in a standard game? So 2-3 pitches per game are being called based on race?

 

The funny part about that is that the article implies intetional discrim. on the part of the umpires. Accordingly, the theory goes that the home plate ump decides to discrim against blacks on 2-3 times out of 250 opportunities. Sure - that makes sense.

[LetsPlayTwo]

1% is rarely statistically significant.

[UBlink]

It's been a decade or 2 since I had statistics, but there is a distinction between the statistical significance of a predictive variable and the size of the impact. For example, I think it would be easy to show that the weight of a driver has a statistically significant effect on fuel economy - meaning that after you've taken everything else into account, a heavy driver will tend to get worse gas mileage than a light driver. The effect will undoubtedly be small, probably much less than 1%, but with a large enough sample size it would also be statistically significant. But it would still be insignificant from a practical basis.

 

The 1% number probably means that only 1% of the calls are close enough for race to be a factor, but within those 1% race as a predictor is statistically significant.

[Bull]

It's been a decade or 2 since I had statistics, but there is a distinction between the statistical significance of a predictive variable and the size of the impact. For example, I think it would be easy to show that the weight of a driver has a statistically significant effect on fuel economy - meaning that after you've taken everything else into account, a heavy driver will tend to get worse gas mileage than a light driver. The effect will undoubtedly be small, probably much less than 1%, but with a large enough sample size it would also be statistically significant. But it would still be insignificant from a practical basis.

 

The 1% number probably means that only 1% of the calls are close enough for race to be a factor, but within those 1% race as a predictor is statistically significant.

 

I agree. Take out the obvious balls, the strikes swinging (less check swings) and the foul strikes, and you're probably looking at a much higher percentage.

[CuseCubFan69]

It's been a decade or 2 since I had statistics, but there is a distinction between the statistical significance of a predictive variable and the size of the impact. For example, I think it would be easy to show that the weight of a driver has a statistically significant effect on fuel economy - meaning that after you've taken everything else into account, a heavy driver will tend to get worse gas mileage than a light driver. The effect will undoubtedly be small, probably much less than 1%, but with a large enough sample size it would also be statistically significant. But it would still be insignificant from a practical basis.

 

The 1% number probably means that only 1% of the calls are close enough for race to be a factor, but within those 1% race as a predictor is statistically significant.

 

Plus, maybe they should have studied specific umps and their calls and not just the group as a whole.

[FergieJ31]

Here's the paper:

 

http://www.eco.utexas.edu/faculty/Hamermesh/Baseball4Authors.pdf

 

One word: LOL ( I guess that's three )

 

This paper is a joke. For instance, not once does he even mention a standard error for any of his point estimates, let alone calculate one. We have gems like this:

 

The effect of racial/ethnic preferences on winning probabilities is even more striking when we disaggregate by umpire race/ethnicity. With White umpires the home team wins 54.4 percent of the time if its starting pitcher is White, but only 52.9 percent of the time if he is not. In the case of Black umpires, the corresponding percentages are 72.7 percent and 55.1 percent, although there are only 11 games in which a Black starting pitcher is evaluated by a Black umpire. In the 36 games in which both pitcher and umpire are Hispanic, the home team wins 61.1 percent of its games, compared to 52.0 percent if the pitcher is non-Hispanic.

 

So he looked at about 11 games with a black starting pitcher and a black home plate umpire. 11 games. And he cites a percent based on that. If you flip a coin 11 times, the expected number of heads is 5.5+/- 1.65, making the one-standard deviation error bar a whopping 15.1 percent.

 

Seriously, this guy should give back his PhD. Utterly irresponsible.

[pete the dog]

1%= 1 out of 100. There are usually, what, about 250 pitches combined between the two teams in a standard game? So 2-3 pitches per game are being called based on race?

 

The funny part about that is that the article implies intetional discrim. on the part of the umpires. Accordingly, the theory goes that the home plate ump decides to discrim against blacks on 2-3 times out of 250 opportunities. Sure - that makes sense.

 

 

 

I didn't see where they made it look intentional. It certainly doesn't need to be intentional to be real.

 

As for the statistics, I assume if the paper was published that this is a statistically significant effect. It would be nice to have information about the effect size, but those of you claiming a 1% difference can't possibly be important are just plain wrong. Small effects can produce big disparities in results. A few marginal calls going one way or another in a game can make a huge difference.

 

Why are people so defensive about this stuff (same author reported a similar effect in basketball)? Is it really that hard to believe? We know that there are subtle (unintentional) racial biases in law enforcement, judges' sentences, medical treatments, loan decisions, housing decisions, and on and on and on. Few of these effects have huge effect sizes, but how many people need to receive poorer treatment before it's important? When you're talking about large numbers of people, a small effect (e.g., 1% of cases) affects a whole lot of people (1% of 1 million instances is 10,000 people). How many marginal pitches do you think there are in a season?

[Dirt Dog Sparly]

Hummm lets see...

 

1)A strike called by the book or by the umpires prevailing strike zone that day?

 

2) Did they include balls that were called strikes?

 

3) What metric did they use to observe the strike zone in question one?

 

4) How long did they observe/ how many looks did they take before deciding a ball or a strike on a pitch?

 

5) Are balls put in play counted in the strike calculations? Ie: Think Duncan over the weekend ending the inning by swinging at the pitch that hit him.

 

6) How well did the people working the study understand and apply correctly the rules of the game?

 

I'm sorry but I cant consider this person and their team seriously after this series of studies.

[UBlink]

Here's the paper:

 

http://www.eco.utexas.edu/faculty/Hamermesh/Baseball4Authors.pdf

 

One word: LOL ( I guess that's three )

 

This paper is a joke. For instance, not once does he even mention a standard error for any of his point estimates, let alone calculate one. We have gems like this:

 

The effect of racial/ethnic preferences on winning probabilities is even more striking when we disaggregate by umpire race/ethnicity. With White umpires the home team wins 54.4 percent of the time if its starting pitcher is White, but only 52.9 percent of the time if he is not. In the case of Black umpires, the corresponding percentages are 72.7 percent and 55.1 percent, although there are only 11 games in which a Black starting pitcher is evaluated by a Black umpire. In the 36 games in which both pitcher and umpire are Hispanic, the home team wins 61.1 percent of its games, compared to 52.0 percent if the pitcher is non-Hispanic.

 

So he looked at about 11 games with a black starting pitcher and a black home plate umpire. 11 games. And he cites a percent based on that. If you flip a coin 11 times, the expected number of heads is 5.5+/- 1.65, making the one-standard deviation error bar a whopping 15.1 percent.

 

Seriously, this guy should give back his PhD. Utterly irresponsible.

 

Table 3 shows standard errors for all of the point estimates, the most controversial of which is statistically significant. In particular, using the LPM model, the standard error of the .00341 estimate is .0017. It's the .00341 estimate that drives the 1% effect described, since 32% of called pitches are strikes. I didn't bother to calculate an appropriate t-statistic, but with N>1,000,000 and reverting to my grad school presumption that all t-statistics are 2, the effect appears to be statistically significant.

 

Note that the impact of pitch count is dramatically greater than any race effect. Again, the measured effect of race is extremely small, but statistically significant. I'm sure discrimination lawsuits have been won using less persuasive evidence.

 

I think their PhD's are safe. Also, note that this is a discussion paper, not a refereed published work. I'm sure the authors would be interested in any criticism prior to submission for publication - see the first two words at the top of the paper.

[FergieJ31]

Table 3 shows standard errors for all of the point estimates, the most controversial of which is statistically significant. In particular, using the LPM model, the standard error of the .00341 estimate is .0017. It's the .00341 estimate that drives the 1% effect described, since 32% of called pitches are strikes. I didn't bother to calculate an appropriate t-statistic, but with N>1,000,000 and reverting to my grad school presumption that all t-statistics are 2, the effect appears to be statistically significant.

 

Note that the impact of pitch count is dramatically greater than any race effect. Again, the measured effect of race is extremely small, but statistically significant. I'm sure discrimination lawsuits have been won using less persuasive evidence.

 

Yes I've sent them comments. I guarantee I'm not the only one calling foul on these guys. I have a few problems with the paper:

 

There is a voluminous body of research on racial bias, a less emotionally charged word than discrimination, which these authors use in the title. There is no overt claim in the paper that the effect they study is the result of willful conduct, so why did they put racial discrimination front and center?

 

And yes, Table 3 is where statistical significance of their main argument is examined. But if you read the paper, time and time again they try to support their argument with utterly insignificant statistics, e.g. the 11 games I mentioned in my previous post.

 

And re Table 3 my question is, where are the results for White umpires?! Why did they only cite t-stats for less than 10% of the cases, the games called by Black and Hispanic umpires? They admit to leaving out White umpires without justification or any attempt to explain why. It's not hard to guess: their tenuous claim to significance probably evaporated quickly when they added the 90% of the games called by white umpires.

 

And they say this:

 

While none of the coefficients on the umpire race/ethnicity indicators is statistically significant, some suggestive patterns emerge from the first three panels. In Columns 1-3(a), both estimates of the 7

coefficients on the Black and Hispanic umpire indicators are negative, suggesting that pitches thrown by White pitchers are less likely to be called strikes by non-White umpires.

 

No, your results are either significant or they're not. You are not allowed to say things like "suggestive patterns emerge" and other weasel words in an academically honest paper.

 

Also, note that this is a discussion paper, not a refereed published work. I'm sure the authors would be interested in any criticism prior to submission for publication - see the first two words at the top of the paper.

 

Who said it was published? It would have been much more impressive had it been peer-reviewed and submitted for publication before calling up MSNBC (note the publication date and the date MSNBC reported the story), rather than throwing it out there with a "COMMENTS WELCOME" slapped at the top.

 

Another ridiculous quote:

"The results suggest that standard measures of salary discrimination that adjust for measured productivity may be flawed, and we derive the magnitude of the bias generally and apply it to several examples."

 

Really?? The results purport to prove MLB umpires employ racial discrimination in their ball/strike calls. Isn't a stretch to extrapolate "wage discrimination" metrics from pro athletes making $500k/yr and up to standard cases?