Potential Variance in Season-Long Results

Wondering if anyone has repeated seasons in which all 12 teams are identical...and developed a sense for potential variance in wins/losses for any team? In other words, might my disappointing 70 win club (on which several players batted 40-50 points below what I typically see for them in other leagues at that cap) be an 85 or 90 win club with better luck?

GG:
I haven't done that in the online game but can tell you from replaying leagues with identical teams in face to face play that the difference between results of the different seasons is usually quite large. I expected to see less variance in the online game and while don't have data relative to the exact same teams, can tell you that the variance I've experienced is still very large relative to individual players.
I don't know how helpful any of that is but I too would be very interested in hearing the results of anyone who has experience in regards to the online version and replaying seasons. Ultimately it would seem like one of the most important things to know about an individual player's card would be how great that variance is as that would greatly affect a card's value and therefore the card's draft value as well.
For the 2017 Player's Championship I tried to draft some of the same guys repeatedly to gain some insight into the variance and found some pretty interesting data. I had Goldschmidt multiple times and while his batting order and teammates of course would affect his results, just by looking at batting average his season results were:

.282, .283, .280 and .275 - I figured safe to count on around those numbers but in the playoffs up to this point(thru 123 games) he's batting a shocking .225

Sandy Leon batted .268, .289, .306, and .277 for me in full seasons

On the pitching side Tanaka had era's of 2.60, 2.92, 3.08, 3.45 - so same with the pitching side of things and would br nice to be able to run the cards through a hundred seasons or so as soon as they are released to be able to gauge how wide of a disparity there is as there is times it might make more sense to draft a players that is very likely to bat between .280-.290 rather than the guy who might bat .340 but could also end up batting .250 on the season.

Hope that made sense and hoping someone out there has done more research into the variances and will be willing to share as we all have our favorite cards/columns to use but I know I at least would like to have some data to back up those decisions.

there can be quite a bit as while it works out about 50-50 pitcher card vs hitter card only the hitter side stays static as whom you face in each game can vary even replaying a season....I have had aces knocked out early and then teams feast on depleted bullpens etc.

I agree completely. Lots of variables that not only affect the statistics but that also make the game fun. Saying that, I still have always thought and think you'll agree that there isn't always a lot of consistency in regards to player cards and their regular season results. We all have our favorite card that performed better than it should have or drafted a guy that we expected to have a killer card only to be sadly disappointed. Running the simulations repeatedly I think would provide good insight into which guys are more likely to over or under perform and which guys are more likely to come close to their season stats and that was the point I was trying to offer up.
I was actually thinking someone out there probably does this and would be great to be able to take a look at those results -- I think it would definitely affect my draft list.

the sheer number of variables...who you play when, pitcher fatigue etc.. It was noted in one league that after facing a particular hard hitting team many teams had another bad series as their pitching staff was used up in the previous series..
I had a team where in my division I faced one team's ace pitcher only 2 times and caught the number 4 and 5 pitcher 8 times ....made a difference in the final standings

GG:
I haven't done that in the online game but can tell you from replaying leagues with identical teams in face to face play that the difference between results of the different seasons is usually quite large. I expected to see less variance in the online game and while don't have data relative to the exact same teams, can tell you that the variance I've experienced is still very large relative to individual players.
I don't know how helpful any of that is but I too would be very interested in hearing the results of anyone who has experience in regards to the online version and replaying seasons. Ultimately it would seem like one of the most important things to know about an individual player's card would be how great that variance is as that would greatly affect a card's value and therefore the card's draft value as well.
For the 2017 Player's Championship I tried to draft some of the same guys repeatedly to gain some insight into the variance and found some pretty interesting data. I had Goldschmidt multiple times and while his batting order and teammates of course would affect his results, just by looking at batting average his season results were:

.282, .283, .280 and .275 - I figured safe to count on around those numbers but in the playoffs up to this point(thru 123 games) he's batting a shocking .225

Sandy Leon batted .268, .289, .306, and .277 for me in full seasons

On the pitching side Tanaka had era's of 2.60, 2.92, 3.08, 3.45 - so same with the pitching side of things and would br nice to be able to run the cards through a hundred seasons or so as soon as they are released to be able to gauge how wide of a disparity there is as there is times it might make more sense to draft a players that is very likely to bat between .280-.290 rather than the guy who might bat .340 but could also end up batting .250 on the season.

Hope that made sense and hoping someone out there has done more research into the variances and will be willing to share as we all have our favorite cards/columns to use but I know I at least would like to have some data to back up those decisions.

Hey Timothy,

My guess is that given a sufficient sample size, variance will be nearly identical across Individual players. Goldschmidt’s BA across the four seasons you referenced was tighter than I would expect, so I’m not surprised you found an outlier in another sample...too bad it was in the playoffs!

Over the course of a full season, would you guess that as much as 25% of all the games come down to one or two plays? So if you’re really unlucky in that set of chances, say you only have 15 out of 50 go your way, that can make a pretty big impact on your team’s record.

In a playoff series just concluded AJ Burnett gave up 3 HR’s to RH hitters in two starts, all on a 6,5 roll, 1-3 split! Assuming the entire opposing lineup has N power, on each roll, that’s a 3 out of 4,320 probability, less than 1 in 1,000! 3 times in two games? That’s unlikely.

Glenn