Productivity

Recently the productivity statistic in PCTI has generated a fair amount of controversy. There is a faction in PCTI that supports and accepts the productivity statistic as a legitimate and fair determination of a player's basketball value and performance. However, there is a growing and vocal minority in PCTI that rejects the productivity statistic as a biased and arbitrary performance metric that does not adequately evaluate a player's on-court performance. Some have even suggested that I arbitrarily assigned productivity scores to players to suit my own ulterior motives. And yet, even though there are competing factions in PCTI with respect to productivity, one cannot help but realize that generally, and with few exceptions, that the best tournament performers typically grade out with a high productivity number while the worst performers grade out with a meaningfully reduced number.

That being said, let me mention a few things before I get to the actual statistic. One, the productivity statistic was taught to me by my 7th grade basketball coach, who learned it from Coach Wooden at UCLA. Two, the productivity statistic cannot measure all of a player's contribution to a team. For example, it does not measure a player's energy level, teammate chemistry, IQ, or how hard a player competes, all of which are important player metrics. And third, it has limitations. In other words, it does not measure if a player makes the hockey assist, nor if his ability to defend discourages a player from being aggressive, nor what type of condition a player is in, nor any defensive breakdowns a player causes. So once you acknowledge these limitations, we are ready to proceed to the quantitative productivity metric.

Here it is. The productivity metric is derived by assigning one point for every positive contribution a player makes that can be measured. So one point for every FG made, FT made, board, assist, block, steal, and an additional point for every 3 ball converted. Then subtract one point for every negative contribution a player makes like a missed FG, missed FT, and turnover. The sum of these two contributions is a player's overall productivity score. You can quickly deduce that the productivity statistic gives equal weight to each contribution, even though we all know that not all basketball statistics are equal. For example, a FG made in PCTI is generally much more valuable than is a blocked shot out of bounds, even though they are given an equal scoring weight.

So you can see why a player like Esk generally scores well in productivity because he shoots a high percentage, rebounds, drops dimes, and gets steals and blocks. Meanwhile, a player who typically doesn't make contributions in all of the categories that we measure would see a reduced score. While I readily admit that the metric itself has shortcomings and limitations, and cannot possible measure a player's true worth to his team, I find it instructive that with only a few exceptions it is a relatively accurate guide to determining who had a productive tournament and who did not. So hopefully this puts the baby to bed. Sabin