I am not questioning that your statistics are incorrect. I hope that my response was not taken as such. I was attempting to relay my confusion when looking at stats like this showing a large discrepancy. I have seen these and It needs to be looked into , but if it is a crisis then what is causing it ? I believe I know what you meant by it but there is no truth without the cause of stats. Well without a meaning behind them. For example I am going to just throw random guesses out there . More black males enlist in the military which if true would put black males in an environment with loaded weapons more than white females. Gangster songs describing and fantasizing about murder are written and sales targeted toward the black youth rather than young white females. Black males live in low income high crime areas where being shot is more likely than white females. White females are much easier to see on a dark night in a police shootout than a white female. I am sure there is a little truth in all of those suggestions but I don’t believe they are the answers that portrait the picture that was intended when these stats were polled and published. if someone didn’t know american football and they were told to bet on the teams come Sunday that will surely run the ball 30 or more times they will win. They always win, this is what the announcers tell people. They may go bet on every team they feel has a chance to run over 30 times that week. After they lose their bets I can tell then I have a statistic that is %100 sure to win. I t ell them to bet on the teams that take a knee 3 times in the second half. I promise that bet will win %99.9 in match up. if they carry on like this they will just look at another stat until they lose everything and will never have a marginal chance until they stop to ask why the hell one team wins over another. Someone who doesn’t know why a stat looks out of place does not know if it is wrong or not. They are left only to try to right things by knee jerk emotional reactions ,gut feelings, and yes turning a blind eye until they have some insight into the data.