This week's column deals primarily with the statistical scarcity and volatility of fantasy categories. Before explaining those ideas and diving into the numbers, let’s take a quick look back at some conclusions drawn over the past three weeks.
In last week’s column, Values and Trends, it was shown that points and weighted FT percentage were highly concentrated early in fantasy drafts for 2013-14. Steals, rebounds and assists all showed a predictable and steady drop-off across the top-100 players, but value-added players could still be found in these categories throughout the middle rounds and (occasionally) beyond the top-150. Three-point shooters were readily available in the middle-to-late rounds, as were players capable of raising your fantasy team’s FG percentage. Blocks were primarily concentrated in the first few rounds, though eight outliers offered at least +1 standard deviation between picks 100-150.
The week before that, in Busts and Values, guards were found to comprise the majority of the season’s premier ‘value picks’ (e.g. Lance Stephenson, Isaiah Thomas, Jodie Meeks) while forwards and centers dominated the list of the biggest ‘busts’ (e.g. Omer Asik, J.J. Hickson, Ersan Ilyasova). The top-216 players, similarly, included slightly more guards than forwards, with centers predictably scarce in leagues that require two Cs on each active roster. A few rookies broke through for substantial value, such as Michael Carter-Williams and Ryan Kelly, but the vast majority was worthless for fantasy purposes. It was also found that the middle rounds of fantasy drafts, rounds 5-7, were riddled with ‘busts’ and under-performing fantasy picks, whereas rounds 8-12 provided more reliable value relative to Average Draft Positions.
Most of the above conclusions were derived from my overall top-216 rankings, which showed a tendency for SFs to provide late-round value in nine-cat leagues, where their low turnovers are an underrated asset. A close examination of those rankings shows interesting splits between each player’s eight-cat and nine-cat rankings, and you can peruse them at your leisure.
There are more interesting takeaways, but let’s jump ahead to the focus of today’s column—statistical scarcity and volatility. Back in October I identified 3-pointers, blocks and assists as the categories with the greatest 'scarcity', which is to say they were concentrated in a relatively small group of players and/or showed wide variations from player to player. That analysis was based on a small sample size early in the season, however, so I’ve decided to revisit the concept to determine if my original conclusions held up throughout the season.
Number of Players Exceeding the Mean
The title of this section explains a simple way to understand the concentration of statistics across fantasy players, in this case the top-170 nine-cat options from 2013-14. Before looking at how many players raised the mean in a given category, let’s quickly look at what those means were for the relevant top-170 population:
FG Percentage: 46.30%
FG Attempts: 11.29
FT Percentage: 76.80%
FT Attempts: 3.34
The chart below excludes FG and FT figures. It also lists the number of players below the mean for turnovers, which is the only category in which more than half of the top-170 players ‘improved’ upon the mean. The second-most readily available category was 3-pointers, in which nearly half of the population (83 players) raised the mean. The number of value-added players dwindles as you read the categories from left to right, and once again shot-blocking proves to be the category concentrated among the fewest number of players.
This highlights the appeal and rarity of players who average 1+ blocks per game, guys whose defensive contributions are easy to overlook such as Terrence Jones, Amir Johnson or Pau Gasol. It also suggests that a turnover machine like Russell Westbrook or John Wall can be compensated for as the draft progresses, since there are tons of guys who average below the mean 1.88 turnovers per game. Three-point shooters may also be less of a priority early in drafts considering the number of viable options averaging at least 1.04 triples per game. Although this is an easy way to visualize the hunt for value-added players across fantasy categories, it is an incomplete analysis. Knowing that a player raised the mean only tells us so much – it suggests the amount of statistical concentration and scarcity but doesn’t capture the degree to which players raised the mean. This is where standard deviations (SD) come in.