Other Sites to Aid Your Basketball Education

The good folks over at Give Me The Rock (one of the best basketball blogs out there) were kind enough to post a nice writeup of RotoPoll tonight:

For those who are statistically inclined, check out the RotoPoll Blog for fantasy analysis you can get lost in – including discussion of the most average fantasy player, the value of a missed shot, and some pretty slick player pages (complete with graphs).

Aw, shucks. They also mention Basketball Monster, an intense stat site with a lot of useful tools too. If you haven’t either of these sites before, go check them out.


6 Responses to Other Sites to Aid Your Basketball Education

  1. mabeuf says:

    Thats for the shout outs. I have been lurking the work that you do here and love what you do. Most specifically, i love the detail you pay to the most ‘insignificant’ of players. Please keep it coming!

  2. rotopoll says:

    Thanks, and will do. By the way, if anyone has ideas or suggestions, for example on analysis they’d like to see, send an email or just post a comment.

  3. docpaul says:

    This is an amazing site. I am a statistics freak, and this combined with your AJAX wizardry make this a “must visit”. I’ve always wondered if one could arrive at a way of predicting performance for a given player based a running average scoring system such as yours combined compared to how the opposing team “matched up” with that player in the past. IE, Arenas is playing Orlando tonight.. how would you predict his averages would move based on his prior performance playing Orlando?

  4. rotopoll says:

    You’re very kind. Spread the word!

    As for your question… it’s very intriguing. It’s the kind of thing that would be fun to explore. I’m guessing that it will be a lot harder to get meaningful results than some of the stuff we’ve already done (which is simple by comparison), because there are so many other factors… injuries, lineup changes, back-to-back games, off-court issues, and so on. But it would be unbelievably cool if it worked.

  5. docpaul says:

    RE: spreading the word, I’ve already done so!

    RE: performance prediction, I’d imagine that the first step would be to start capturing opponent data (IE, matchup history for each player). Maybe start with team comparisons, but then if you have access to full box scores and player lists, you could maybe even get down to “average lineup ratings” using your scoring system. IE, according to your evaluator, Chauncey Billups is facing a Pacers starting lineup tonight with an average 0.83 rebound score, 1.87 block score, and a -1.24 steal score (here’s the link: hp://tinyurl.com/ye8x58)

    There’s got to be some significance to how your team average defensive scores “game” a given player’s offensive performance and perhaps the converse is even true.

    Other suggestions: take advantage of rotowire.com’s RSS feed and link the last few news items for each player to your corresponding player page, since you seem to be a RSS wizard.

    On your AJAX search bar, it might be helpful to allow city initials “ie, IND”, to arrive at players as well. You could be smart enough to append those onto lists when three letters are typed.

  6. rotopoll says:

    What it sounds like we’re headed toward here, and I apologize to any true stats wizards out there since I’m a little rusty, is a complete regression analysis across all the stats, looking for factors correlated with total overall performance. There are probably of lots of factors that affect performance that we don’t even know about. That would be a serious undertaking. If anyone has any better ideas or thoughts on how to refine this, I’m all ears.

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