The first week of the NBA season is the most important for securing fantasy titles. By the time the sun sets on day 7 the waiver wire will be barren of potential trophy fish. Doubtless no few dinks, guppies, and leather boots will have been swept up as well. But that's a professional hazard when trawling for potential league winners.
Week one's importance only heightens my disappointment when I open this sub for discussion about the first few games of the season and find discussions that are, broadly speaking, unhelpful; largely insipid bickering about what is or isn't an over-reaction. This is my contribution to that bickering.
I'm interested in three questions:
Given that ADP is a strong predictor of performance, how many games must a player play before it is more useful to know their actual production than their pre-season ranking?
How much do we learn (relative to ADP) from each of a player's first N games?
Given a player's ADP, the number of games played, and their stats during those games what should we expect them to average over the remainder of the season?
Data
We're looking at ADP based on Fantasypros' average for the 2022, 2024, 2025, and 2026 seasons. 2023 was omitted because I couldn't source rankings for that year (I've since acquired it but haven't updated). I included the top 250 players (by projection) for each year.
We're comparing ADP against season-long averages calculated according to Yahoo's default points setting. I know most people play in category leagues, and this won't exactly translate, but those approaches are highly correlated. Additionally, I pulled game-by-game stats for the first 5 games of the season from BBall Ref. When comparing the first N games against a season long average, the latter is adjusted by removing the first N games.
I omitted any player who played fewer than 20 games in a season. Otherwise, I made no attempt to exclude players who suffered injuries or (perhaps more importantly) benefited from injuries to their teammates. As we're looking at over- and under-performance this is an important source of (non-linear) variance. But it's really hard to control for, so I didn't.
ADP and Actual Performance
Below is a plot of ADP and season long averages. Two things are important: firstly, draft position are a reasonably strong predictor of fantasy production (r2 = .7); second, the relationship is non-linear. Accordingly, we'll be using ln(ADP) going forward.
GRAPH OF ADP AGAINST FANTASY POINTS/GAME
ADP versus First N Games
After how many games is it more useful to know a player's actual fantasy production than they're pre-season ranking. This question is straightforward, and knowing the answer would be extremely useful.
The table below lists the r2 of each players average fantasy points over their first N games (up to 5) against their points/game over the remaining season.
TABLE 1
The relationship between a players season-long production and a single game is, unsurprisingly, noisy. However, after just two or three games it becomes appreciably strong and by their fifth game there is a stronger correlation than there is with pre-season rankings. That correlation should continue to strengthen until reaching an upper bound in the middle of the season.
Very Simple Projections
Distant as we are from the middle of the season there is no reason to discard the useful information contained in ADP. The chart below shows the r2 of a series of multi-variate regressions that include both ADP and early season production.
TABLE 2
Adding even a single game modestly improves the performance of the model (p<0.001). An output of this approach is a series of simple formulae which, given a player's ADP and current production, outputs their expected fantasy points per game over the rest of the season.
The table below shows those projections, specifically the top 10 over- and under-performers relative to pre-season projections.
TABLE 3
As you can see, even an exceptional pair of games (Paul George) to begin the season only moderately increases the expected value of a player's remaining season.