Pace is defined as the number of possessions a team uses per game (48 minutes). Over the past 10 years, the league average for pace has risen from 92.1 to over 100(!) last season. It follows that a team playing at a faster pace (and thus using more possessions) will likely produce more fantasy points. It also follows that a team playing AGAINST a team that plays at a high pace will likely get more possessions, and thus produce more fantasy points. But does this actually translate? And should we be looking towards pace when building our DFS lineups?

The first thing I did was look at opponent pace vs. points scored over the first half of the season. Did players playing in a 'pace up' matchup actually score more fantasy points on average? To do this I first averaged all player scores at each salary level, and against each opponent pace (at the time the game was played). I then standardized all player scores to the $7,000 salary level.

**Example:**

Players priced $6,500 have scored an average of 36.34 points against opponents ranked 22nd in pace.

Standardized by dividing 36.34/6,500 and then multiplying by 7,000.

Gives us ~39 points on average.

After standardizing all scores to the $7,000 salary level, we can compare how players performed against opponents with different ranks for pace, all else being equal. See below:

As expected, players playing against teams that play a higher pace scored more fantasy points. This starts to add some validity to the idea that 'pace up' matchups are important factors to consider in NBA DFS. However, this doesn't tell us the whole story. I decided to look further into this by breaking our sample into two groups. Players over $8,000 and players under $7,000. (I played around with these thresholds a bit to find the most noticeable results).

The first group I wanted to look at is expensive players, or stars. My initial theory was that stars would see even MORE of a boost from 'pace up' matchups, as they would likely be taking significantly more shots and finding themselves on the end of more rebounds and assists.

So, I was shocked to find out that there was very little correlation between points scored by players over $8,000 and opponent pace. One thing I will note from this graph is that stars playing in high pace matchups on average seem to have relatively high floors, but there was too much deviation to make any real conclusions from this graph. I suspect this is largely because stars will get theirs regardless of the matchup. They are far less dependent on extra possessions to put up their usual numbers and typically take a consistent amount of shots game to game.

The next group I wanted to look at was players under $7,000. Now knowing that stars performed similarly regardless of opponent pace, I suspected that the correlation we had seen in the first graph was driven by cheaper players.

And boy was I right, there is a VERY significant correlation between cheaper players and high pace matchups. My theory here is similar to that of before, but in those games with extra possessions, the extra possessions aren't going to the starts, who will get their touches regardless. Instead, they are going to the role players, who step into expanded roles in games that are played at faster paces.

So, what can you (or I) take away from this moving forward. I think what it shows the most is to not over value a star player playing in a high pace matchup, or on the flip side, undervalue a star in a low pace matchup. Stars will get their touches regardless of the games pace and the players who truly benefit from faster games are the ones who might be getting overlooked.

**Our 'DFS Dives' series aims to take an in depth and analytical look at popular DFS statistics to see if they REALLY make a difference in player performance. **

*Have a stat or question you want answered about NBA DFS? Email us and we will select our favorite question to cover in an edition of our 'DFS Dives' series! Exclusive to AC Plus members!*

If you've ever played DFS (or any fantasy sport), then chances are you've faced a tough decision between two players, and your final decision came down to the little green (or red) number next to the players matchup. The well known defense verse position (DvP) metric has been widely accepted as the primary source to consult when considering whether a player has a good or bad matchup.

On the surface, DvP makes sense. **If a team has given up more points on average to a certain position, then they are more likely to in the future, right?** Unfortunately not. The standard DvP metric you see on popular sites fails to account for multiple *crucial* factors. For one, certain players are better than others, and have different salaries (see Salary Adjusted DvP). But second, and perhaps just as important, positions are becoming less and less relevant in the NBA each year. You have guys like Porzingis and Drummond both being listed as centers, despite playing two COMPLETELY different roles. At Analytic City we attempt to solve this problem with our proprietary player profile DvP metric.

Simply put, each player in the NBA is given a classification (player profile) based on how they score their FGs, how they accumulate fantasy points, and how many minutes they play. Let's look at an example:

** Player: **Andre Drummond, Center (Big)

** Hypothetical FG Scoring Profile:** 45% from the restricted area, 35% from the paint, 18% from midrange, 2% from three.

** Hypothetical Fantasy Point Accumulation:** 41% from scoring, 40% from rebounding, 10% from assists, 9% from defense.

* Hypothetical Minutes Per Game: *30.2 MPG

**Final Classification:** Paint_Big-Rebounder-Starter

In all, there are 20-25 total final classifications we use based on various thresholds we have set.

*From this, we can create our Player Profile DvP metric by looking at how players with the same player profile have performed against a players opponent in past games. To read more about Player Profiles and how they are constructed/used, click here.*

Now for the million dollar question, our player profile DvP metric sounds and looks awesome on the surface, but does it actually have any predictive power? I decided to use the second edition of our DFS dives series to take a look.

The first thing I did was filter the data into what I believe will give the most accurate picture as to whether our metric has predictive power. I limited our sample to only the top 50 salaried players from every slate, and also removed any player who played fewer than 10 minutes. This should give us a really clean dataset to look at, as we won't have to deal with player injuries, or things like cheaper players who may have performed extremely well due to expanded roles (in which case DvP data is hardly relevant). That being said, it also means the results of this study can only be extrapolated to higher salaried players, and are less relevant to cheaper/inexpensive DFS plays. After filtering the data from the first half of the season, I was left with 1320 entries. Before running any regressions,* I graphed the value created from each players Player Profile vs each players Fantasy Points Scored*. Value created is defined as the difference in dollars per point between that profile against the players opponent and the league average. In other words, how much cheaper have players with the same profile been against the player in question's opponent when compared to the league average? A positive value indicates players with that profile have been cheaper for each point scored, while a negative value indicates players with that profile have been more expensive for each point scored.

I was incredibly excited to see a noticeable positive relationship between the two variables. You may be thinking to yourself "That barely looks like anything", but it is important to keep in mind the HUNDREDS of other factors that go into every NBA game, so creating a statistic with predictive power is incredibly difficult (there are very few of them). And from an initial look, it seems as though we may just have done that! For reference, here are some other matchup based statistics that I have found to have some (although how much is still in question) predictive power in NBA DFS:

- Pace (for players under $7,000)

- Over/Under

- Salary Adjusted DvP

End of list. I am sure there are more, but my point is that the list of matchup based metrics you can use to help you make NBA DFS lineup building decisions is very limited.

To test whether or not there was a statistically significant correlation between these variables, I ran a linear regression.

The values with the yellow background above are what we care about. You can see in the bottom left that the slope of our line is 0.0267, which means that for each 1 point increase in the value of our player profile, you can expect a 0.0267 point increase in fantasy points scored. Bringing this to the extremes, the difference in expected fantasy points scored for a player with a value of -50 from their player profile and a value of 50 from their player profile (an extremely bad matchup vs an extremely good matchup) is a whopping 2.67 points! The next thing to look at is how confident we are in these results; our given P-value of 0.0235 indicates that our results are statistically significant at the 5% level, a commonly accepted threshold for statistical significance". A p-value of 5% or lower is often considered to be statistically significant." (investopedia.com) Simply put, a correlation exists!

If you're using our projections, good news! We account for Player Profile DvP in each and every player point projection (unless the sample size is under 10). But even if you aren't, my main takeaway is this: *Looking at the value gained (or lost) from each players player profile should be one of your primary tools when considering if a player is in a positive matchup in NBA DFS. *

**Our 'DFS Dives' series aims to take an in depth and analytical look at popular DFS statistics to see if they REALLY make a difference in player performance. **

*Have a stat or question you want answered about NBA DFS? Email us and we will select our favorite question to cover in an edition of our 'DFS Dives' series! Exclusive to AC Plus members!*

]]>