Hollinger needs 24 games to forcast teams (the difference between Boston and Miami) This was better than Vegas, which is apparently the gold standard, by three games. This was a full six games better than the best Wages of Wins model, which is what people are focused on.

 

However, as I mentioned, the key is not that any of these models is best. Rather, it's that they all fail! We're relative creatures, so we want to say - look Bovada did better than Schoene! But in this case, that doesn't matter. The range of games you need is so large, the information is meaningless!

 

A book that everyone purports to have read is "The Signal and the Noise" by Nate Silver. A topic Nate brings up is "Unknowable Unknowables" As the name pretty much says, these are things that you don't know and more importantly, can't know. For instance, Steve Nash got injured this season. No one could have known about this ahead of time and yet, it clearly impacted things. George Karl's decision to not play JaVale McGee, despite the fact he got a major contract, was not knowable ahead of time to anyone.

 

When making predictions, we are making assumptions about many things. One of the things we know pretty well is player evaluation. If a player was good last year, they will probably be good this year. However, even this is unexact. Players perform differently as they age. And of course, rookies are notoriously hard to predict. We have a limited number of things we have a firm grasp on. So it's not surprising that we are bad at predictions.

Updating vs. Predicting

What's key about this is to stop using predictions as the end all be all test. Hollinger is another great example. In the middle of the season Hollinger went to the Memphis front office. And the Grizzlies, who are now in the conference finals, made several moves to their teams. Of course, Hollinger could not have known about these to start the season when he made his predictions. And yet, these moves had some influence on the Grizzlies' success. Using the best data at the time and updating our "predictions" as things progress is the right method. And that's why using metrics that have the best combination of

• Telling us what happened.
• Being consistent over time.

Are useful. We can use them to guage what is happening and use them to update our analysis about teams. Trying to become "perfect" at predicting just won't happen. Hollinger has "beaten" Vegas three years now. He hasn't improved the range of games he needs to do it though. And, as I mentioned, that range is rather large. The number of moving parts in a season is vast. It's good to give judgements about the state we think teams are in. Being able to accurately guage how they'll do after 82 games when injuries, trades, breakouts, breakdowns, etc. occur though? It's simply not going to happen.

-Dre