Actually it doesn't. I did a research/article on this for another website about 3 years back, and divided the games by 0-1 runs, 2-3 runs, 4-5 runs (being average) 6-7 runs, 8-9 runs, or 10 or more runs. What I found (to my surprise) was that the teams that scored a lot of runs, but did so with a lower slugging percentage actually were more to the extremes, having more games where they'd score 0-3 runs, but also more games where they'd score 8 or more. This caught me completely by surprise in all honesty, to see the so called 'slugging' teams show more consistency in their run scoring distribution. It's not on this computer, it's on my old PC downstairs, so I'll look later and see if I can dig it up and share it. You might have found that to be true for a particular sample but I don't really see how that's possible in reality. If you picture the most extreme examples of each, you have a team that only hits HR and a team that only hits singles. You can quickly simulate that in excel and I would think you'd find the HR team to have a higher variance. Of course, If I am going to throw out that hypothesis, I should just test it, huh? My suspicion is that the difference in variance is so small between the two that you would need a massive sample to see the difference. As for what is the average runs/game variance, there are plenty of ways to estimate that based on average runs/game. Seems like baseball fans are always surprised by how often their favorite team scores 3 runs or less. Here's an old blog post of mine addressing fans' criticism of the 2006 Brewers offense: http://rluzinski.blogspot.com/2006/05/runs-per-game-and-consistency.html I think it has to do with fans' expectation that runs/game follow a normal distribution? It simple can't as you can't score less than 0 runs per game but you WILL score 10 or more runs at least a few times. That means that your average runs/game might be 4.5 but you will score less than 4 runs in more than 50% of your games. That's just reality.