Why steal against elite-armed catchers?

hit and runs that don’t pan out are an excellent source of CSs, since the successful H&R is most useful with that hole between 1b and 2b, and there are many more RH [than LH] low power hitters who might be putting the ball on the ground rather than going for extra bases. the H&R is likely losing some of its strategic value as batters who can guarantee they will connect with a pitch are declining in the modern game, where even SSs hit 26 homers per season, but then strike out 22% of the time. baseball simulations would want to account for this trend in having the general population of MLers less able to connect than in the days of enos slaughter, leo durocher, rabbit maranville, etc. it is very difficult to determine from typical baseball stats how many outs and hits are resulting from H&R attempts and SAC grounder attempts. i see that stats inc and bill james DO have some hitting data re bunts. simulations should definitely have players rated for H&R ability, the better rated guys much less likely to swing and miss, giving the opposing catcher a potential CS. i would suggest a higher H&R rating for those with very low strikeout rates.

Thanks to you folks, I seem to have the answer to my original question, the answer being that many (most?) of those CS against catchers like Pudge are actually failed H&R.

Curt brings up a fascinating, related point about sim design.

I’ve seen two different, general approaches to Hit and Run in sims:

1. Give each batter a H&R rating on a scale of 1-3 or 1-4. The rating is presumably based on K rate. Then take a random number and look up the result on a H&R Chart.

versus

2. Calculate the batter’s result normally, as though it were not a H&R, then convert the result using a H&R chart.

My experience with approach #1 is that it can give unrealistic results, in part because such a limited number of H&R ratings clumps all batters into only 3 or 4 H&R results categories, and in part because a single H&R rating cannot adequately represent all of the aspects of hitting: K-rate, ground ball rate, drive rate, fly ball rate, HR rate, walk rate.

To give an extreme example, I’ve seen dead ball (read: low-K) mediocre batters (BA around .200) qualify for the maximum H&R rating, thereby ‘earning’ an effective H&R BA of around .350. BTW, the ‘.350’ number is not from simulation result; that number is derived from the H&R chart itself. These games’ H&R charts are typically not era-adjusted, although the stats that the players’ H&R ratings are based on are era-adjusted, of course.

Approach #2 has advantages: i. there is excellent granularity in terms of individual results; ii. individual results are not one-dimensional, but reflect all aspect of the batter’s ability; and iii. the batters’ ‘base’ abilities (before the H&R conversion) reflect their era (for example, low-hit/low-k vs high-hit/high-K, etc), then are translated to H&R results.