Life In 19x19

wineandgolover wrote:But I think your baseball analogy isn't very useful for two primary reasons.
1) Baseball is a team sport, which by its nature is different than individual sports and games like go.
2) Today's era in go doesn't correspond with today's era in baseball at all. In baseball, you have several countries that play well, but only one that is dominant. Many, if not most, of the best players eventually go to MLB to prove themselves, and, yes, to earn the big bucks.

This is one of the reasons I tried to use pitchers as the basis for comparison. Pitchers performances are highly individual based and most modern pitcher evaluations will remove external effects (team defense, park factors, etc). A pitcher is a one on one contest much like go, there is perhaps a weakness in the analogy in that pitchers do not directly compete with each other instead they are evaluated by proxy. When evaluating how a pitcher is expected to perform, they use rate stats to assess his past performance (something like FIP, fielding independent pitching), regressed statistics to predict how he should have performed (xFIP - FIP but normalized for places the pitcher may have gotten lucky, like having a large number of flyballs but low number of home runs), and counting statistics trying to estimate overall value (WAR or Wins Above Replacement - it compares both rate stats and the total amount of time played in a season so that you get a total value produced). In theory you could try to derive similar metrics like this for go, normalizing wins based upon the context. Blitz wins might not count as much as wins with long timesettings, wins in later rounds may count more, wins may have more or less value based upon the state of a series (Is it easy to put away an opponent when they are facing elimination? or is that a game where the person who's ahead tends to take a breather and give up a loss?). Ideally putting everything into a normalized context could help you project expected performance, and maybe find places where players got lucky.

The other amusing reason I picked this analogy is because baseball pitching has this literal exact dilemma going on right now (which I alluded to in my previous post). There is a pitcher from the Japanese Leagues who was absolutely dominant last year and they need to project how well he will do when he makes the transition to MLB. Masahiro Tanaka went 24-0 and posted very strong "traditional" baseball stats over 212 innings pitched (2.29 FIP if you care to look at that...lower number is better, like an ERA). Of course the challenge is projecting how moving to bigger ballparks with stronger hitters and a ball with more bounce will affect his performance. Luckily there are people who run the numbers and do the projections, and they think he'll end up being somewhere around the 25th-35th best pitcher in the league.

The overall analogue to go is quite striking. Japan's baseball leagues are good, but generally considered not quite as strong as the US. There is only limited mixing between the two groups, but there are some comparisons that could be made for reference. Hiroki Kuroda is sometimes given as a good comparison for Masahiro Tanaka, he was about 22nd or 23rd in WAR last year depending on who you ask. If we use Dr Bae Taeil's ratings and we figure Iyama falls somewhere in the 20-50 range of best players, that's actually about what they're expecting from Tanaka as a pitcher both from projections and from comparisons...it's actually a little funny how these things seem to parallel. Of course the one problem we have moving over to go is that there really isn't a good recent comparison for Iyama that we can use to assess outcomes in international play, the last time someone was this dominant in Japan the international go scene was also dominated by Japan. Perhaps he will make the jump and we can use him as the baseline for future players.