Rob Vollman raised an interesting question in the comments section of my last post, that being whether my findings precluded the possibility that some teams consistently perform better or worse in the playoffs.

The question can be answered by comparing each team's actual performance, as measured by winning percentage, with what would be expected based on regular season results. If the spread in [actual - expected] winning percentage is significantly greater than what would be expected by chance alone, then that suggests that some types of teams may consistently outperform or underperform in the playoffs relative to the regular season.

As with my last post, my sample consisted of all 1882 playoffs games played between 1988 and 2010. I've prepared a chart which shows, in the leftmost section, how each of the league's teams performed during that span. The middle section of the chart shows each team's expected wins and losses, based on single-game probabilities generated from regular season data. Finally, the rightmost section shows each team's winning percentage differential (defined as observed winning percentage minus expected winning percentage), as well as the probability of observing a differential at least that large by chance alone.

That last part may require some elaboration. All 1882 games were simulated 1000 times, based on the regular-season derived probability values. For each of the individual simulations, I determined each team's winning percentage and subtracted from it that team's expected winning percentage. The p value column simply indicates the proportion of simulations in which the the absolute value of that number - that is, the team's [simulated winning percentage - expected winning percentage] - exceeded the absolute value of that team's [observed winning percentage - expected winning percentage].

A specific example may be illustrative. Anaheim had an observed winning percentage of 0.576, an expected winning percentage of 0.462, and therefore an [observed winning percentage - expected winning percentage] of 0.114. In only 0.033 of the 1000 simulations did Anaheim's simulated winning percentage differ from its expected winning percentage by at least 0.114. Hence Anaheim's p value of 0.033.

As can be seen, some teams outperformed their expected winning percentage, whereas others underachieved. Based on each team's [observed winning percentage - expected winning percentage], and the probability of each differential materializing by chance alone, Edmonton, Pittsburgh and Anaheim were the three most "clutch" teams, whereas the Islanders, Columbus and Atlanta were the biggest "chokers." But is the spread between the teams any different from what would be predicted from chance alone?

There are two ways in which this question can be answered. The first is to group the observed winning percentage differentials ( expected versus actual winning percentage) into several categories, and calculate the number of values in each category as a percentage of the total sample (relative frequency). Following that, the same can be done with the simulated differentials. The two distributions can then be compared.

The second is to repeat the exact same exercise, but to use actual wins instead of winning percentage. I prefer this second method as the fact that some teams, such as Atlanta, Columbus and Quebec, played very few games has the potential to skew the results if winning percentage is used.

Here are the two graphs:

In the case of winning percentage, the actual spread is noticeably greater than the observed spread. But the difference is not too large, there being something of a general correspondence. And in the case of wins, the two lines form almost a perfect match.

If I were to issue a conclusion, it would be that although some teams over or underperform in the playoffs relative to their regular season results, this appears to be mostly the product of normal statistical variation. There isn't much support for the idea that there exists an ability to perform in the playoffs that is independent and separate from the ability to perform during the regular season.

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## 6 comments:

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Your prediction is very good, very detailed, I think no one can reach you this analysis positioning, I only use cheap gold gw2 to get somethings.

You are right but there are some things that they are unpredictable that you can measure and it makes a huge impact to the team.

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