Here, instead of using individual years, I used the average OPS differential and average winning pct for all 30 teams over the last 5 years.
The regression equation from using individual years was
Pct = 1.325*OPSDIFF + .5
The r-squared was .827 and the standard error was .029. Over 162 games, that is 4.639 wins
The regression equation from using the 5 year average was
Pct = 1.3465*OPSDIFF + .5
The r-squared was .869 and the standard error was .017. Over 162 games, that is 2.72 wins. That is a big drop from the first regression. In a given year, luck will play a role. But the more seasons and data that are used the more accurate the relationship. By combining the years, some of the good and bad luck evens out.
The table below shows the prediction for each team. It seems strange the 6 most extreme teams are all pretty far from the rest of the pack. The Orioles were predicted to have a .476 pct but it was actually .505. That means they won 4.762 more games per season than their OPS differential would estimate.
Here is a graph of the relationship