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The Weekly Nichols: What the Regular Season Can Tell Us

Among the many reasons the Magic were able to defeat the Cavaliers was the simple fact that they match up so well against them. Orlando’s style and personnel was the right combination for beating a team that was so dominant in the regular season. This was manifested in the season results between the two teams. Similarly, Orlando was 2-0 against the Lakers. Does that mean we should pencil them in for the championship? How much do matchups matter and how important are prior regular season results?

To answer these questions, I first collected some data on every playoff series from the past three years. For each series, I recorded the difference in the seeds (a 1-8 matchup would have a difference of 7), the result of the regular season series, and the result of the playoff series. I then ran two regressions: one on the relationship between the seed difference and the playoff result, and one on the relationship between the season result and the playoff result. Below I’ve posted the two graphs:

Seed vs. Playoffs
Season vs. Playoffs

In the first graph, the seed differential is on the x-axis and the playoff result is on the y-axis. In the second graph, the season result is on the x-axis and the playoff result is on the y-axis. In both of the charts, the season and playoff results are quantified on a -4 to 4 scale. A 4 would mean that the favorite won four more games than the underdog (a 4-0 sweep), and a -4 would mean the opposite.

There are a couple of interesting observations. The team that won the regular season matchup failed to win the playoff series in just four of the 44 series that took place over the last 3 years (there are a few regular season ties). This is indicated by points in the top left or bottom right quadrant of the second graph.

As we can see, there were seven instances when the underdog won the regular season series (indicated by the seven points to the left of the y-axis; some are hidden because there are doubles). Five of those times, the underdog pulled off the upset.

If we compare the R^2’s of the two graphs, we see that season results are actually a slightly better predictor of how a playoff series will go than the difference in the seeds is. Of course, both of the R^2’s are very low and the difference is quite negligible. But the point still stands: if you want to predict how a playoff series will turn out, you’re slightly better off if you go through the teams’ previous matchups that year than if you just look at how different their seeds are.

I should end this article with a few notes of caution. First, there are plenty exceptions to the rule. Second, everything must always be taken in context. Regular season results could be skewed by injuries or odd circumstances.

Personally, I think Orlando will win the Finals in seven games.

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"Regular season results could be skewed by injuries or odd circumstances."

and the fact that the Lakers only give a full effort against the big name teams.

Orlando was not.

Jon,
Thanks for the response and good work. I'm always wary of questionable statistical analysis and it looks like this is not the case. No offense to you or your work, I'm usually wary if no mention of a p-value or significance is made.

Good point re: binary vs net. Thanks again and great analysis.

"What’s the p-value of those two tests?"

The p-value of the first one is .0139. The p-value of the second one is .0079.

"It looks like inter-conference series losers, the only ones that can have 2-0 results, the loser of the series wins 1/3 times. One would think that inter-conference series have less predictive value than intra-conference series due to there being only two data points. "

The small sample size is indeed a concern for the inter-conference (Finals) series. That's definitely one of the cautions you have to have when looking at the data.

"Finally, isn’t treating the win-loss of a series as the delta of wins misleading? Shouldn’t the Y be a binary variable, few care if the series ends in 4 or 7 as long as they win."

I chose not to do a binary variable because I think there is some analytical value to how many games a series was won in. Obviously the end goal is just to win, no matter how many games it takes. But a 4-game sweep is a lot more convincing than a 7-game battle because the latter can sometimes be decided by a few breaks going either way. In a four game series, it is much clearer who the better team is.

interesting, but r² of 0.15 (or anything below 0.9) are usually about as reliable in predicting anything as... say, cardboard chairs.

great website, though. will become a daily read!

Nice... thanks for doing this. There are a lot of Lakers fans out there displaying a little too much confidence. I'm a Lakers fan and I believe they can win, but I sort of wish everyone had picked against them. It's weird... last year they were the upstarts who beat the West and they got picked over a team with 1 certain and 2 possible (probable?) Hall of Famers and lots of veteran experience, not to mention a ridiculous regular season record. They had been swept in the season series v. the Celtics. Now this year they are the experienced team who everyone expected to be here, with a great regular season record, but they got swept in the season series, and everyone is picking them again. I don't get it how these "experts" do this. But it should be a great series.

What's the p-value of those two tests? It looks like inter-conference series losers, the only ones that can have 2-0 results, the loser of the series wins 1/3 times. One would think that inter-conference series have less predictive value than intra-conference series due to there being only two data points. Finally, isn't treating the win-loss of a series as the delta of wins misleading? Shouldn't the Y be a binary variable, few care if the series ends in 4 or 7 as long as they win.