BIGDAWG
Introducing BIGDAWG
This season picklytics is adopting a new player evaluation model that looks to value a number of baseketball skillsets and really highlighting individual performances. BIGDAWG or Basketball Impact Generator: Distribution Aware Weekly Grade seeks to assess players relative to the maximum contribution in all categories based on weekly performance.
BIGDAWG VS Z-score
In the previous 3 seasons pickle picks were determined by utilizing aggregated z-score on player per game contributions with a 3 game minimum. Within the fantasy basketball community there has been discussion on how z-score is not a valid evaluation metric for basketball production as it is indented to be used on normally distributed data. In the modern day NBA stat productions follow a very skewered distribution meaning that star players generate much more scoring and other countable over the majority of their peers. The results in low event statistics such as 3s and blocks could throw very large increases in z-score which biased scoring to heavily favor big men and shooting point guards.
BIGDAWG seeks to limit this by normalizing all weekly statistics against the maxima and not the mean. This prevents players from generating excess value in categories and allows for strong consistent multi category showings to still be valued highly.
How this works is the top performer is found for each category. the BIGDAWG score for the category then becomes
Score(player)/Score(max) * Category Weighting.
In Addition there are additional parameters included that seek to score based on positive possession as well as across the board peripheral generation.
In the BIGDAWG player info we then see Good stats as Green and bad stats as Orange.
BIGDAWG Smith - Breaking down the new metric
Here we see BIGDAWG Smith a second string Center from the Chicago Bulls Based on his weekly performance we can see he received a BIGDAWG rating of 246. On the left we see the player portrait and name with position and score. On the right the FT/FG are broken into Volume and Efficiency stats. We can see based on league averages that Smith was a very efficient low volume shooter. From a free throw perspective we can see that he had a moderately high volume at terrible efficiency. When it comes to counting stats we can see that Smith had fairly low production through the week. The one exception is turnovers which is a stat that is punitive. These items indicate that Jalen Smith may not be very good at basketball.
Behind the scenes the maximum stats for each category are calculated a value based on category weight (all categories are considered equal except TOV) that ranges between 1 and the maximum. These individual scores are all aggregated and to produce a final rating. A rating of 246 puts Smith in the top 180 players for the week. That is not a very big dog at all.