In the world of fantasy basketball today, a player's value is defined almost entirely by his numbers. Sure, experienced managers could take into account other factors as well, such as a player's health or behavior. For example, I can be sure I will never invest such a high draft pick in damaged goods like Andrew Bynum
, nor will I reach for troubled children like DeMarcus Cousin
s, who insist that hitting below the belt and putting the ball in the hoop are one and the same game. In rotisserie formats, such knowledge is sufficient to build a contender. However, in head-to-head leagues, the last puzzle piece remains: dynamics.
From a fantasy perspective, dynamics refers to the tendency to deviate from the average. In other words, it is a player's ability to "explode." Because basketball is dynamic in its nature, player performances vary game by game. Thus, averages are not dependable in head-to-head formats where the scope of evaluation rests within a small sample size (three or four games in a given matchup). This is where dynamics shines. While consistency is desirable for percentage categories (field goal and free throw), dynamics in volume categories (points, rebounds, assists, steals, blocks, and three-pointers made) puts a team on top.
If dynamics is reflected in performance, and if performance is recorded in box scores, then surely dynamics can be quantified into user-friendly statistics for fantasy players to use as well. The question remains as to how. A common method of measuring variance in statistics is by calculating standard deviation. While this measures a player's tendency to deviate from his average, this is not necessarily beneficial in fantasy because it does not take into account a player's inconsistency. Take two numbers for example: 7.49 and 6.60. These are the standard deviations for Brandon Jennings
and Kevin Durant
in terms of points scored each game this season (as of December 24, 2012), respectively. While Jennings has the higher standard deviation of points compared to Durant, calling Jennings a more dynamic scorer from a fantasy perspective (or from any perspective, for that matter) is ludicrous. Jennings' high standard deviation in this case was a measure of his inconsistency, not dynamics. For fantasy purposes, a different algorithm is required to calculate a player's dynamics, to take into account both explosiveness and sustainability.
Introducing Chua's Sustainable Dynamics Rating (SDR)
Chua's Sustainable Dynamics Rating (SDR) is a statistical measurement of a player's dynamics in various volume categories (points, rebounds, assists, steals, blocks, and three-pointers made). SDR takes into account game-by-game performance as well as sustainability of production over stretches of consecutive games. A high SDR implies a large likelihood for a player to explode in a specific statistic for a given matchup in a head-to-head format. Players with a high SDR for multiple categories are desirable in fantasy teams. Note that SDR is not a measure of efficiency, and it does not take into account categorical averages. SDR can be relatively compared intra-category, but not necessarily inter-category. Below, I demonstrate the significance of SDR for each category from a fantasy perspective. All statistics are based on games played this season, as of December 24, 2012.
For the points category, I compared Chris Bosh
(dynamic) to Rudy Gay
|Category||Chris Bosh||Rudy Gay|
|Sustainable Dynamics Rating (SDR)||25.30||18.64
|Highest combined points (4-game stretches)||90, 89, 89, 85, 81||87, 87, 87, 83, 82
|Highest combined points (3-game stretches)||71, 71, 70, 70, 66||70, 66, 66, 61, 59|
As seen above, Gay has a slight advantage in points per game compared to Bosh. However, Bosh's significantly higher SDR makes him potentially much more dangerous than Gay in head-to-head matchups. Bosh's highest combined point totals in four-game and three-game stretches (the lengths of most matchups) surpass Gay's totals by a large amount, despite Bosh averaging fewer points per game. This translates to a higher scoring ceiling for Bosh, which is beneficial in head-to-head leagues.
Listed below are the league leaders for points per game, in descending SDR.
For the rebounds category, I compared Larry Sanders
(dynamic) to Pau Gasol
|Category||Larry Sanders||Pau Gasol|
|Sustainable Dynamics Rating (SDR)||20.03||9.12
|Highest combined rebounds (4-game stretches)||50, 42, 41, 40, 39||42, 41, 41, 38, 36
|Highest combined rebounds (3-game stretches)||41, 38, 35, 32, 32||36, 31, 28, 28, 28|
As seen above, Gasol's relatively large advantage in rebounds per game (0.6) is nullified by the dwarfing of his 9.12 SDR to Sanders' 20.03 SDR. When comparing the players' highest combined rebound totals in multiple game stretches, Sanders clearly demonstrates superior rebounding potential.
Listed below are the league leaders for rebounds per game, in descending SDR.
For the assists category, I compared Monta Ellis
(dynamic) to Kirk Hinrich
|Category||Monta Ellis||Kirk Hinrich|
|Sustainable Dynamics Rating (SDR)||10.78||7.74
|Highest combined assists (4-game stretches)||32, 29, 27, 27, 27||29, 26, 26, 26, 25
|Highest combined assist (3-game stretches)||24, 22, 21, 21, 20||23, 22, 20, 20, 20|
Hinrich averages more assists per game compared to Ellis. However, as indicated by a lower SDR, Hinrich's ceiling of effectiveness is limited in matchups. This is evident when comparing Hinrich's highest assist totals during stretches of games to Ellis'.
Listed below are the league leaders for assists per game, in descending SDR.
For the steals category, I compared Kemba Walker
(dynamic) and Jason Kidd
|Category||Kemba Walker||Jason Kidd|
|Sustainable Dynamics Rating (SDR)||6.18||4.57
|Highest combined steals (4-game stretches)||15, 14, 13, 12, 9||11, 11, 10, 9, 9
|Highest combined steals (3-game stretches)||14, 11, 10, 7, 7||9, 8, 8, 8, 8|
Listed below are the league leaders for steals per game, in descending SDR.
For the blocks category, I compared Robin Lopez
(dynamic) and Joakim Noah
|Category||Robin Lopez||Joakim Noah|
|Sustainable Dynamics Rating (SDR)||7.09||4.36
|Highest combined blocks (4-game stretches)||13, 13, 12, 11, 11||12, 12, 11, 11, 11
|Highest combined blocks (3-game stretches)||12, 10, 10, 9, 9||10, 9, 9, 8, 8|
Listed below are the league leaders for blocks per game, in descending SDR.
This is precisely why Larry Sanders could easily make his case for waiver player of the year—the ability to explode in multiple categories (rebounds and blocks for Sanders) is scarce in the waiver wire.
For the three-pointers made category, I compared Klay Thompson
(dynamic) and Kyle Korver
|Category||Klay Thompson||Kyle Korver|
|Three-Pointers Made||Dynamic||Not Dynamic
|Sustainable Dynamics Rating (SDR)||6.49||4.60
|Highest combined 3pt made (4-game stretches)||15, 15, 15, 15, 14||15, 13, 13, 13, 12
|Highest combined 3pt made (3-game stretches)||13, 12, 11, 10, 10||11, 11, 11, 10, 9|
Listed below are the league leaders for three pointers made per game, in descending SDR.
Applying the concept of dynamics when drafting in head-to-head leagues is crucial. Having players who are capable of exploding over multiple stretches of games can turn the tide even in the least favorable of matchups. Therefore, arming a team with an arsenal of highly dynamic players to go with players who produce consistently is the key to building a true fantasy contender. Only those that understand this truth will be best equipped for the long and trying season.