The Monte Carlo simulation models real-world risk: deals are correlated (bad quarters hurt many deals at once), early-stage deals frequently slip to next quarter, and large deals often close at reduced scope. These factors create a left-skewed distribution. There are more paths to missing the target than exceeding it. A median outcome near target with a lower hit probability means you will probably land close to target, but the downside scenarios are heavier and more numerous than the upside ones. In other words, when things go wrong they tend to go wrong together, pulling many simulations below the line even though the central tendency looks healthy.