What is a Player Profile?
At Analytic City, we use advanced stats to create a player profile for each player based on the way they score and accumulate their fantasy points. From this, each player is given a specific classification. These classifications are then used to create our proprietary Salary Adjusted Defense vs. Player Profile Metrics and to adjust our projected point values.
Editor's Note: See our Salary Adjusted DvP article Here if you are still unsure why we need to adjust for salary or how it is done.
Okay, that was a bit complicated, let's break it down.
I'm going to start with an example: Take a look at these two images below and notice what stands out.
Shot Charts, KD 2018-19 vs. Lebron 2012-23. (Photo credit to @Kirkgoldsberry)
Despite both these players playing SF (KD can be listed at PF, but for the sake of the argument let’s assume he is a SF), they score in entirely different ways. In 2019, Durant did substantially more of his scoring from beyond the arc and midrange, while in 2013, Lebron tended to score from inside the paint. KD's scoring profile would thus be different from Lebron's. By using advanced statistics, we are able to see the percentage of a player's field goals they score from different areas on the court. From this, we classify players differently. Players with more than 60% of their field goals coming from 3 point range, for example, are labeled as "Pure_3PT", whereas big men with greater than 80% of their buckets coming from in the paint are labeled "Paint_Big" Those are just two of the many examples, but hopefully this is starting to make some sense.
NBA superstar Shaquille O'Neal (pictured above) is a perfect example of a player who would've been classified under "Paint_Big". With a career three point record of 1-22.
We don't stop there. Scoring isn't the only way players can accumulate fantasy points. We also further classify players into 1 of 3 groups. "Scorer", "Rebounder", or "Other". A scorer is defined as any player who accrues the majority of his fantasy points from scoring, rebounder from rebounding, and other from assists and defense. We attach this classification to our previous one to create each player's final profile. For example, Andre Drummond's current classification this season is "Paint_Big_rebounder".
Here are a list of the scoring classifications we use:
“Paint_Big”, “Stretch_Big”, “Guard_Paint”, “Pure_3PT”, “Three_and_Key”, “Midrange_Specialist”, “All_Around”, and “True_Shooter.”
What Can We Do With Player Profiles?
Player profiles are an interesting way to see who is scoring from where, but they also provide incredible value for DFS purposes.
Imagine a scenario where Lebron is playing against the Jazz, and Rudy Gobert (the Jazz center) has been a monster defensively in the paint all year. From a fantasy perspective, we would of course still be interested in how SF's have done against the Jazz, but we would be even more interested in how SF's who typically score the same way as Lebron have done against the Jazz. Perhaps the Jazz would still be a good matchup for 2019 Durant due to his outside shooting ability, but a bad matchup for 2013 Lebron as it will be tough to score around the rim due to Gobert's shot blocking presence. By looking at how past players with the same profile have performed against a players opponent, we can start to get a better sense of whether or not a player is in a strong matchup from an opponent perspective.
From this, we create our Salary Adjusted Defense vs Player Profile metrics, which, I believe, is the most valuable metric in all of NBA DFS. Take a look at another example to understand why:
Imagine that on back to back nights, the Mavericks and the Cavs are playing the Clippers. We want to know whether Drummond and Porzingis, who are both listed as centers, have a good matchup against the Clippers. As of this writing, the Clippers are 1st in salary adjusted defense versus position, meaning you have to pay the most $ per point at the center position against the Clippers. If you just looked at that, you would write this off as a terrible matchup for both players. However, when playing against players classified “Paint_Big”, the Clippers rank only 12th. This is a huge discrepancy, the Clippers have been the best in the league defensively against big men who stretch the floor (“Stretch_Big”s), but when it comes to bigs who score most of their points from the paint, they are middle of the pack. If you just used salary adjusted DvP, you might have thought the Clippers were a terrible matchup for Drummond, and faded him despite him looking like a great value play. In reality, the Clippers would have presented an average matchup. On the other hand, Porzingis would be in a terrible matchup either way. Remember, both these guys are listed at center, but they have two completely different play styles!
You can find complete access to Salary Adjusted Defense vs Player Profile numbers in our newsletter Here through the downloadable datasheet. In that sheet, you will see that rather than providing a ranking we provide the average dollars per point ($/PT) allowed by the opponent to players with the same profile. This serves to give a more accurate reflection of the scale of just how good (or bad) a player's matchup might be. Remember, a higher $/PT is a bad thing from a fantasy perspective, it means you have to pay more for each point. (read more about that Here) You will also notice data is not available for certain players, which is because their opponents have not yet faced 10+ players with the same profile (the sample size is too small).
Note: In the newsletter data, many of these restrictions are implemented, most notably a minimum of 15 minutes played for the data from that player to be counted.