| 7 | grivfmd1 | ML | 95-67 | .586 | 1st | No | Yes | yes | yes | yes |
| 8 | grivfmd1 | ML | 81-81 | .500 | 3rd | No | No | | | |
| 9 | grivfmd1 | ML | 102-60 | .630 | 1st | No | Yes | yes | no | no |
| 10 | grivfmd1 | ML | 62-100 | .383 | 4th | No | No | | | |
| 11 | grivfmd1 | ML | 88-74 | .543 | 2nd | Yes | No | no | no | no |
| 12 | grivfmd1 | ML | 97-65 | .599 | 1st | No | Yes | yes | yes | yes |
| 13 | grivfmd1 | ML | 60-52 | .536 | |
Also Cooperstown - year 10 is the same year Mike's team "collapsed" - almost no changes in the team between yrs 7 to 10 and only moderate changes from 10 to 13 (some youth movement at positions but pitching essentially the same after year 10 trades).
Not saying that teams are programmed to loss but that they may be programmed to exceed, mirror, or disappoint compared to their potential. In year 8 one of my star players had a "career" year - so to me it seems unlikely that team variation is due solely to player variation.
I agree with the regression to the mean phenomenon but suspect it operates on a yearly (or 1/2 year? at the all-star break?), not on a purely random basis. This is one of the reasons I rarely "tear down" a disappointing team. It would have to happen 2 years in a row before I would threw in the towel on a team I thought should be descent.
I suspect you will see this occurring more often in competitive leagues where the difference between teams is inherantly less and therefore swings in records tend to be greater with even subtle changes in the team or the "engine". (for example - the pop in year 12 could have been the change in the HR programming - or could have been something else - but the team "took off" after the all-star break after being blah up to that point)