Didn't the statistics just say that white 3-5 has a winning record in Chinese counting with modern komi?



I would be interested in seeing the statistics categorized by rank for the opening to see if the winning percentages are indeed affected by rank, to answer the conjecture that there is a difference between amateurs ability to utilize a specific opening.

I would suspect that beginners and weak amateurs wouldn't do as well using 3-5 because there isn't much information regarding how to play those openings, but that there would be substantial variation in play due to so many other issues during play. I would expect a bit of an advantage for strong amateurs playing 3-5 due to the not mastering every opening and not consistently playing competition that uses it, and this effect would diminish as people get stronger and have encountered more of the openings.

Why didn't you include 3-3 in your question?

This raised an interesting point that I can't really deal with in depth (at least yet). But I have wanted to get back to it for some time with a little factoid and to raise the question whether it is the statistics that are vulnerable to bias or just our memories?

The point is "...and Kato with the Chinese style...". This caused one of those "hmmm..." moments that tend to send me scurrying off to GoGoD/Kombilo, because I recalled that in the 2nd Kisei every game began with the Chinese.

Sure enough we see that Kato was quite successful playing the High (sorry I was too lazy to be thorough) Chinese back when it dominated the Japanese tournament scene, relative both to his overall results with Black and to other players' results with the same fuseki:

So maybe we have something! But wait. We remember specifically that Kato liked to play the HC. However, at that time so did everyone else (OK, not quite everybody but many of the top-flight players that Kato was facing, e.g. Fujisawa Shuko). What about Kato's impact on the statistics from the opposite side? How did he do against the HC?

This tells us that Kato was just about as much better than his average when playing against the HC as he was playing with the HC! It also shows us that our selective memory is based on only 56 of the 93 games that Kato played involving the HC.

If we compare the stats on the HC with and without Kato we can see the effect he had on the overall stats:

So we see that he did have an impact, boosting the Black winning % by 0.5 percentage points. As to the significance, I will leave that for the reader. (I did the analysis just for the fun of it.) As always YMMV.

Note: the "All" figures here are filtered for the period 1964-2005 to match Kato's professional career.

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Dave Sigaty
"Short-lived are both the praiser and the praised, and rememberer and the remembered..."
- Marcus Aurelius; Meditations, VIII 21

I think this is a fantastic point. My take on this is that this is simply a result of the model we are using when we simply take a win-percentage based on a given opening. But really, I think that was is happening in the general case with this type of analysis is a maximum-likelihood estimation based on the sample data.

Currently, there is only a single input variable used in our model: the opening type. To spice things up, we could use a number of different input variables: the opening type, the player, the time period, etc.

With whatever model you select, you could then use something like logistic regression, for example, to predict the probability of success given this set of input variables, eg. "If i use the chinese opening, my name is kobayashi, and the year is 1980, what's the probability that I'll win this game?". Contrast this with the current approach of a single variable, where you're saying something much more general, "If I use the chinese opening, what's the probability that I'll win this game?"

I don't think that we can say absolutely that the more general model is bad, however, sometimes having additional input variables like this can help to form more accurate hypotheses given new data.

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be immersed

It's important to note that more information is not necessarily better, as you still have to separate the wheat from the chaff. Malcolm Gladwell has a bit written about this here, if you go down to the answer to question 2.

The real question, I suppose, is which games are representative for statistical modeling of the openings in question, and which are not. I am not sure we will ever have a perfect answer to that.

I agree that more information is not necessarily better. The only thing I might say differently is that the real question is which attributes of games are representative for statistical modeling. A given game could contain many pieces of information that may or may not be useful to a model.

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be immersed

Its too bad the openings I play only have one or two pros to do statistics on, and for *most* of their games they could probably pass once or twice and still win.