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.