Arturo Galletti is the Co-editor and Director of Analytics for the Wages of Wins Network. He is an Electrical Engineer with General Electric in the lovely isle of Puerto Rico, where he keeps his production lines running by day and night (and weekends) and works on sport analysis with his free time.
The sky is also blue.
I know that we tend to harp on this point but it’s worth repeating. We as fans tend to focus on the obvious. The person who throws the football. The person who swings the bat and yes the person who shoots the rock. We remember the makes and forget the misses. This makes us terrible at assigning proper value to the actions of the players in the game and determining their value.
We may have even written some books to that effect (on sale now! :-)).
The point of this post is not to argue whether or not scorers are overrated. I’m treating that as a given. The point is to come up with a systemic way to quantify this effect using math. If I focused on the truly exceptional scorers or players since 1978 — and put in a minute requirement at 1600 minutes –it might look something like this:
If you keep coming back I might even have more on this for you lucky fans! I’m evil like that.
P.S. Some quick explanations for Point Margin Produced (for the full detail go here)
The Wins Produced metric works great when looking over how much a player helped our hurt your team for a season or over their career. When trying to discuss game to game though it can be a little abstract. Luckily the Wins Produced formula is all about converting points (or the difference in points using efficiency differential) to wins so what if we convert wins back to points? It’s easy enough to do with the following formula.
Point Margin = 31 .0 (Wins Produced-Wins Produced by an Average player)
Basically the difference in Wins Produced for a player versus an average player can be mapped directly to point margin (go here if you want the full detail behind that equation). Let’s illustrate this as well (for simplicity I’m using .100 WP48 as the player average, it’s actually .099). Here’s a break down of how that works on a minute by minute basis.
Trotting out a star (0.250 WP48) is like spotting your team 4-5 points. Trotting out a player like Bargnani? Just the opposite. Trotting out an average player doesn’t gain you any points, but it doesn’t lose you any either.
If you want the entire league in a shiny image you can get them all here:
Point Margin for every player in 2011