Quote:
Originally Posted by DotDash
It's been a while since I had the time to do this, but what I used to do (and there may be better / more efficient methods), is go into the Player Search screen for a number of completed tournaments, and filter it so that only players with a relevant number of at bats (or IP) are visible. Then use Report -> Write Report to Disk. Then once you have generated such reports for a number of tournaments, combine them in Excel, sort them by player name, add up the combined stats across tournaments and teams per player, and then recalculate the statistics you think are most important in evaluating a player's performance. I liked to calculate batters' Runs Created per Plate Appearance, and then multiply it by 580 to get an idea of a player's average full-season performance. I don't recall what I used to evaluate pitchers, but the method was the same.
The key here is to not just look at your players' performance, but at the performance of all players in multiple tournaments so that you have enough data to draw conclusions on.
A shortcut to building an average winning tournament team is to look at a number of teams that ended 1st or 2nd, see which players are most common on those teams, and assess whether it is feasible for you to obtain such cards in order to compete at whatever level you are looking at. (Gold tournaments and upwards can get very expensive if you want to field a competitive team.)
Hope this helps. I'm sure some players have streamlined / automated this process, but I'm not sure if they'd want to share their secrets to becoming competitive  |
I haven't dove this far into it so could be way off, but from a strictly maths perspective I think you would also have to exclude any players on your team, as well as any players on a team that played against your team, to avoid biasing the sample. Ideally you'd pick tournaments you didn't enter at all but for a format you play (or are interested in playing).
For example, if you happen to have several low-MOV pitchers on your team (relative to the format), players who play against you will have higher HR totals than you would expect them to play against the field at large. You don't play against yourself so you don't want to know which hitters will do well against a field that includes your pitchers; you want to know which hitters do well against the field of pitchers from every team other than yours. Similarly for opposing pitchers, any differences between your lineup and a more representative sampling of lineups would lead to difference in pitcher performance against you specifically as opposed to against the broader field.
tl;dr don't use data from players on your team or from players on teams that played against your team.