There is a reason that baseball is known for attracting smart fans, and the continued popularity of games such as Diamond Mind show it. Based on actual statistics, the game provides an experience that is about as close as it gets to managing a team’s baseball strategies on the field.

It’s all about the math

But what does the math behind the games show us about the real game? A lot, apparently. No further proof of that is needed than the fact that Tom Tippett, who created Diamond Mind, was hired by the Boston Red Sox. He helped simulate games in advance and provide information to aid in game-time decisions.

However, even Tippett himself told the New York Times that while simulation games are “real close to real-life baseball,” in the end “it isn’t real-life baseball.”

Baseball Strategies

Still, simulation games and the math behind them can provide insight into some of the common baseball strategies made by managers on the field. In short: Are they really worth doing?

Diamond Mind did analysis on some of these common baseball strategies back in 2009, as reported in the New York Times. Some of that is referenced below.

The intentional walk

Teams walk hot batters to avoid them getting a hit in a clutch situation. It also sets up the potential for a double play for the next batter. But is it really worth it to give a batter a free pass to get on base? Even the best hitters make an out the majority of the time. The Diamond Mind analysis found it actually would save a team five runs over the course of a season not to intentionally walk batters.

Later analysis, including from Baseball Prospectus, indicates that intentionally walking the bases loaded actually helps the offense.

The Stolen Base

Stolen bases are fun. A team that can string together a few slap singles and a couple of steals is a team that is likely going to score runs.

However, is it really worth it to steal? After all, getting thrown out at second base and eliminating any chance of scoring can’t be good.

The Diamond Mind analysis reported that the answer on whether to steal or not is “maybe not.” They looked at the run-happy 2008 Tampa Bay Rays and concluded they would have scored 47 more runs by not stealing as much.

Most mathematicians and simulation players (often the same people) agree that a team needs about a 70 percent success rate on steals to make it worthwhile. This analysis shows the cost of getting caught stealing far outweighs the benefit of a successful steal.

Simulation players know what good field managers know: it depends. Many factors go into giving a player the green light to attempt a stolen base. They include, obviously, the speed of the player and his success rate. But it also includes the success rate of the catcher attempting to throw the runner out, the delivery of the pitcher on the mound, the inning and the score of the game.

Understanding probabilities based on those factors – as well as the risk/reward – must factor into making the steal decision.


Bunting involves making an out to move a runner over, usually from first to second base. The cost is an out. The benefit is moving a runner into scoring position. Without diving deep into the numbers, most analysis finds that in order to prove worthwhile, bunting has to be successful more than 50 percent of the time. Diamond Mind research back in 2009 was inconclusive.

So, again, it depends on the skill of the hitter to bunt, the type of pitches being thrown and the defensive alignment.

That last one opens up a whole new issue in bunting, however. Thanks again to data and simulation, many teams now employ a defensive shift to place defenders in the spots where a hitter has shown over time that he is most likely to hit the ball.

That’s the benefit of the shift. The cost is that it leaves a gaping hole, usually up the third base line – a perfect place to lay down a bunt.

So why don’t more players bunt? The data-driven site Fangraphs looked at the issue and reached a conclusion baseball fans will enjoy: because it’s really, really hard to do. Like so many things that ball players make look easy, bunting is incredibly difficult.

The site found that even the best bunters failed the majority of the time. And the type of sluggers that most teams put on the shift to defend are typically not among the best bunters.

So, the data shows that many of the popular moves made by teams are actually not all that effective – depending on circumstances. And “depending on circumstances” is why games are worth watching, and simulation games are worth playing.