Predict winning teams in the Playoffs

This post is a sequel to my last post: Using Regular Season Matchup Records to Predict Winning Teams in the Playoffs. In that post, we used regular-season matchup records to predict which team will advance to the next round of the Playoffs, which logged about 71% accuracy.

In this post, we will introduce two additional methods for predicting team advancement in the Playoffs. We will see how these new methods fare against the original method that utilizes regular-season matchup records.

The first new method is the seed-based prediction. In the Playoffs, teams in each conference are placed in different seeds (1 through 8) based on their regular-season performance. NBA’s seeding arrangement is a complex process, but generally speaking, Seed 1 (highest seed) team has the best regular-season record in the conference, whereas Seed 8 (lowest seed) team has the worst regular-season record.

The following diagram shows how the matchups are arranged based on the seeding.

In the seed-based method, we utilize the following logic:

  • If a team is of a higher seed, then predict that the team will advance to the next round.
  • If a team is of a lower seed, then predict that the team will lose and not advance to the next round.
  • In case of the NBA Finals, whichever team that hosts the first two games at home will win the series.

This seed-based method fared better than the original method of predicting based on regular-season matchup records. The overall accuracy of the seed-based method logged 75%, which is about 4% more than the regular-season-matchup-record method.

I wanted to see if I could increase the accuracy even further by combining the original regular-season-matchup-record method with the new seed-based method. The logic for the third method is as follows:

  • If a team won more games against its opponent and was of a higher seed, then predict that it would win the series and advance to the next round of the Playoffs.
  • If a team lost more games against its opponent and was of a lower seed, then predict that it would lose the series and NOT advance to the next round of the Playoffs.
  • If a team doesn’t meet the above two conditions, then don’t make any prediction about which team will advance to the next round of the Playoffs and skip.

With this final method, I was able to boost the accuracy up to 81%.

Accuracy of Method 1
(Regular-Season Matchup)
Accuracy of Method 2
(Seed-Based)
Accuracy of Method 3
(Combination)
71% 75% 81%

 

The year-over-year accuracies are as follows:

Season Accuracy of Method 1
(Regular-Season Matchup)
Accuracy of Method 2
(Seed-Based)
Accuracy of Method 3
(Combination)
1979-80 86% (12-2-8) 91% (20-2-0) 100% (12-0-10)
1980-81 62% (10-6-6) 45% (10-12-0) 60% (6-4-12)
1981-82 56% (10-8-4) 55% (12-10-0) 60% (6-4-12)
1982-83 75% (12-4-6) 64% (14-8-0) 83% (10-2-10)
1983-84 40% (8-12-10) 73% (22-8-0) 57% (8-6-16)
1984-85 78% (14-4-12) 73% (22-8-0) 88% (14-2-14)
1985-86 92% (24-2-4) 93% (28-2-0) 92% (24-2-4)
1986-87 64% (14-8-8) 67% (20-10-0) 67% (12-6-12)
1987-88 100% (22-0-8) 80% (24-6-0) 100% (20-0-10)
1988-89 67% (16-8-6) 73% (22-8-0) 78% (14-4-12)
1989-90 82% (18-4-8) 80% (24-6-0) 80% (16-4-10)
1990-91 78% (14-4-12) 67% (20-10-0) 88% (14-2-14)
1991-92 64% (14-8-8) 93% (28-2-0) 88% (14-2-14)
1992-93 60% (12-8-10) 73% (22-8-0) 75% (12-4-14)
1993-94 73% (16-6-8) 73% (22-8-0) 88% (14-2-14)
1994-95 67% (16-8-6) 53% (16-14-0) 60% (12-8-10)
1995-96 77% (20-6-4) 73% (22-8-0) 75% (18-6-6)
1996-97 60% (12-8-10) 100% (30-0-0) 100% (12-0-18)
1997-98 55% (12-10-8) 73% (22-8-0) 67% (12-6-12)
1998-99 50% (12-12-6) 67% (20-10-0) 62% (10-6-14)
1999-00 50% (6-6-18) 80% (24-6-0) 60% (6-4-20)
2000-01 78% (14-4-12) 73% (22-8-0) 100% (12-0-18)
2001-02 70% (14-6-10) 87% (26-4-0) 100% (12-0-18)
2002-03 50% (8-8-14) 80% (24-6-0) 80% (8-2-20)
2003-04 67% (16-8-6) 73% (22-8-0) 78% (14-4-12)
2004-05 100% (18-0-12) 73% (22-8-0) 100% (10-0-20)
2005-06 58% (14-10-6) 80% (24-6-0) 78% (14-4-12)
2006-07 75% (18-6-6) 67% (20-10-0) 86% (12-2-16)
2007-08 88% (14-2-14) 87% (26-4-0) 100% (12-0-18)
2008-09 92% (22-2-6) 73% (22-8-0) 100% (18-0-12)
2009-10 67% (16-8-6) 73% (22-8-0) 73% (16-6-8)
2010-11 69% (18-8-4) 67% (20-10-0) 78% (14-4-12)
2011-12 64% (18-10-2) 67% (20-10-0) 78% (14-4-12)
2012-13 70% (14-6-10) 67% (20-10-0) 71% (10-4-16)
2013-14 62% (10-6-14) 73% (22-8-0) 80% (8-2-20)
2014-15 82% (18-4-8) 87% (26-4-0) 82% (18-4-8)
2015-16 69% (18-8-4) 80% (24-6-0) 82% (18-4-8)
2016-17 82% (18-4-8) 87% (26-4-0) 89% (16-2-12)

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About the Author: Howard Song

I’m a data practitioner by day, a web developer by night, a semi-competent swimmer, an active basketball player, a collector of cool ideas, an aspiring entrepreneur, a college dropout but a lifelong learner, and a self-professed nice guy. I love all things basketball, data, programming, and entrepreneurship.

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