What Do the Numbers Say? Probability of the Cavs Beating the Dubs

Ahead of the NBA conference finals this Sunday, many have already come to the conclusion that the Cavaliers and Warriors will meet again in the NBA finals, for the record fourth straight time. For some, this is an exciting rematch. For others, it is another wasted opportunity for good basketball as they expect the Cavs to receive another beatdown. The dubs won 6-4 in 2015, the Cavs came back 4-3 in 2016, and dubs won again 4-1 in 2017.

While the match up has not always been close, these two teams have played a total of 18 finals games against each other, which provides a decent sample for a logit probability model. Using stats from these 18 games,  I created logit models to estimate the probability of a Cavs victory given Cavs’ performance. So, what do the numbers tell us? Is the Cavs on pace for another beating? Or is there a chance that the “new squad” can takedown the dubs?

“We got a fucking squad now” – J.R. Smith

The Data

I gathered data from the 18 finals games the Cavs and the Dubs have played since 2014. The result column has 1 for win and 0 for lose. The other columns contain key game stats: Field Goal % (FG%), 3-point % (3%), total rebounds (TRB), assists (AST), turnovers (TOV), and points (PTS). The three data sets below organize by the game stats by Lebron James (LJ), the rest of the team (R), and the entire team.

Analysis

I created three logit models that estimate the probability of a Cavs win using different game stats as variables. The way to interpret this table is that a unit change in the game stat leads to a certain percentage point change in the probability of a Cavs win. For instance, the Logit Model 1 says that an additional point scored by Lebron James increases the probability of a Cavs win by 9.62%. (Certain coefficients do not make sense such as an increase in field goal percentage leads to a decrease in the probability of a Cavs win. This is likely caused by an outlier game in the 18 games sample) Overall, these three models show that points, assists, and 3-point percentages matter a lot!

Now, here is the fun part. These models tell us the importance of these game stats to the probability of a Cavs win, but we can also plug-in stats to find the probability of a Cavs win. The line below is Lebron James’ average game stat against the Dubs in the Finals. Even with his near triple double performance, Logit Model 1 says that the probability of a Cavs win is only 32.48%!

The plot below shows that if we hold Lebron James’ game stat at his finals average, but vary his game points, then the probability of a Cavs win increases up to 65%.

We already looked at what happens if we plug-in Lebron James’ average finals game stat. The table below shows the probability of a Cavs win based on different scenarios. For instance, if Lebron James performs his best and the rest of the team hits their finals high of 56.76% for their 3-point %, then the probability of a Cavs win is almost guaranteed at 97.43%!

The most important analysis here is to see what happens if plug-in game stats from the series against the Pacers and the Raptors. The results show what our eyeballs already told us. The Cavs better bring their “Lebronto” selves to the Finals if they want to beat the Dubs. If Lebron performs his Toronto average and the rest of the team hits their average 3-point %, then the probability of a Cavs win is 58.44%. If they perform their best, then the probability is as high as 83.09%.

Knowing this is helpful, but what about the probability of the Cavs beating the Dubs in the best of 7 series? The table below is just one of the paths, but things do not look good for the Cavs.

Combining these probabilities with some general statistics class probability work, I came up with the probability of the Cavs and the Dubs winning the chip in 4, 5, 6, and 7 games.

Conclusion

In layman terms, this says that even if Lebron has his average finals performance (which is amazing already) for G1 and G2, the Cavs bring their average and best Lebronto-selves for G3 and G4 at home, and Lebron has his best finals performance for G5, G6, and G7, the total probability of the Cavs winning in 4, 5, 6, and 7 games is only 17.02%, compared to the Dub’s 77.11%.

Yeah, the numbers say this will be another tough June for the Cavs.

What on earth is Phil Jackson doing with the Knicks?

Breaking down Phil Jackson’s bizzare tenure as GM

The NBA is a zero-sum game. For every win a team earns, another takes a loss. For a champion to be crowned, 29 other teams must lose. Every GM has a different way of approaching the game; some are in win-now mode, some stash picks and look to the future, and some are patiently waiting for their blossoming young stars to lead the way. There is no right answer; history has shown us that there is no single guaranteed path to winning a championship.

However, at some point in a GM’s career, whatever strategy he has chosen has to start producing Wins. At some point, your team is good enough, or it’s just pretending (Clippers). At some point, all your high draft picks have to turn into players (76ers). At some point, your #1 picks have to develop into stars (Timberwolves). No matter how clever or innovative a GM is, at the end of the day, the goal isn’t to stash draft picks or assets, the goal is to Win.

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The Newest Trend in Big Men

At the risk of jumping to conclusions after just one week of NBA regular season basketball, we’re ready to declare that a new wave of NBA big men has arrived in the form of 7-foot centers who play like shooting guards. The “stretch” four or “small ball” four has been around for a long time now, and refers to power forwards who can shoot from outside and thus “stretch” the defense. Over the course of the past 10 years, players with those skill sets became more prevalent since the league as a whole began trending toward small ball for a variety of reasons.

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Why is Home Court Advantage a thing? [Part 1]

Using statistics to understand why teams play better at home

As basketball fans know, our beloved announcers all have their pet sayings when calling games: Mike Breen’s “BANG!” after big shots, Mark Jackson’s “Hand down, man down” (which doesn’t really make sense), Hubie Brown’s “Now now, come on now”. One of my favorite announcers though is Jeff Van Gundy because of all his random ideas and thoughts he spurts out on every broadcast.

Usually, a lot of Jeff’s thoughts are just dumb things he says to kill time during blowouts, but there is one point he consistently makes that has interested me for a while. Why do teams always play better at home? After all, the rims are still 10 ft. tall, the ball’s the same, the coaches and players are the same, and the court is still 94×50 ft. of hardwood no matter where you play.  Continue reading “Why is Home Court Advantage a thing? [Part 1]”

#ForgottenFridays – Leon Powe

Revisiting players who have quietly disappeared from the league.

In this weekly series, we revisit players who were once valuable contributors and maybe even well known during their NBA careers, but have since quietly disappeared from the league. The kind of players who make you go “Oh yeah! I remember that guy”.

This week, we will cover a player who had literally 15 minutes of fame – Leon Powe.

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The Biggest Problem with the New York Knicks

Thoughts from a lifetime New York Knicks fan

The Eddy Curry era in New York was one of the worst time as a true Knicks fan. Isaiah Thomas was from Chicago and he felt that Eddy Curry, who was having one of the best years of his life, would morph the Knicks into one of the better teams in the league. Isaiah decided that the Knicks were ready to win now and he was willing to trade the future for players like Eddy Curry. So the Knicks traded 2 first round picks and received one Bulls first round pick. The first round picks the Knicks gave up ended up being one of the best players in the league LaMarcus Aldridge and the newest Knick Joakim Noah. The Knicks received Wilson Chandler with their first round pick, who was a nice role player but never was anything like the other Aldridge or prime-Noah.

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