HiR:tb Toots (@warwalker)

Prediction Update

Red KingI took a bit of heat in the comments, mostly from loving family members, about my failure to accurately forecast the result of Super Bowl XLII.  I was attempting to think of a witty and incisive comeback to silence my detractors but the Juniorbrain was not providing.

Instead, therefore, I took to surfing the ‘Net and found this article by Tuesday Morning Quarterback Gregg Easterbrook at espn.com’s Page 2.  Consider a sampler smidgen:

Just before the season starts, every sports page and sports-news outlet offers season predictions — and hopes you don’t copy them down.

Jay Glazer of Fox Sports forecast Randy Moss would be “the year’s biggest letdown. Moss won’t be nearly as effective as was predicted. Not even close.” Moss set the single-season touchdown receptions record. Glazer thought Lovie Smith would be Coach of the Year and Drew Brees would be league MVP; neither of their teams made the playoffs. Glazer thought the NFC West would be the league’s toughest division; the combined division record was 26-38.

The Wall Street Journal forecast the Eagles, Saints, 49ers, Ravens, Cardinals, Broncos and Jets would make the playoffs; none did. Clifton Brown of The New York Times forecast an NFC championship of Saints over Bears; neither made the postseason. He foresaw the Packers were “likely to finish around .500;” Green Bay hosted the NFC Championship Game. Judy Battista of The New York Times predicted the Dolphins “may be better than last season” and the Broncos “will not miss the playoffs.” 

My strategy now is to agree that  I did some bad on that prediction thing, but as far as epic prognosticating failures go, I have much to learn. 

The end of the article talks about a simple two-step algorithm for picking NFL winners that has proven to be something like 69% effective – as good or better than virtually any “expert” soothsayer.  The algorithm requires no football knowledge whatsoever, just instructions to pick whichever team has the better record;  in the event of a tie, the algorithm demands that you pick the home team.  I haven’t time to write more thoroughly about it now, but back in the day, when I was living in Toronto with my friend “Mark” Downtown “Brown”, we had a pick-em competition each football season.  We played against a gold bust of Elvis that shared the apartment on Queen St. with us;    Downtown and I made our picks based upon our football “knowledge”, whereas Elvis made his picks based solely on the number of Elvis Presley fan clubs per capita in the county in which each team’s home stadium was located (preferring, obviously, more Elvis-philic counties over their relatively Elvis-phobic counterparts).  In the event of a tie, Elvis went with the team whose home stadium was closer to Graceland on an “as the crow flies” basis.   Elvis whupped our asses, badly, each and every year and finished one year with a record of better than 70% against the spread.  Unfortunately for us and Elvis, it was the early 90s and Buffalo loves Elvis more than Dallas or New York, which meant that the King had some dismal Super Bowl results.  Nevertheless, the point was made with me – statues of Elvis are more reliable than print journalists about virtually every topic imaginable.

1 comment to Prediction Update

  • Butter sandwiches FTW!!

    I have a friend at work who, having recently moved from Las Vegas, makes regular return pilgramages during football (NCAA & NFL) season. We discuss point spreads and over/unders along with such diverse factors as prior records against-the-spread, home field (turf or grass), prior performance (no indicator of future returns), psychological motivations, mascots (if you’re going to put in a colorizing, terrorizing adjective, why would you ever use “Golden” or “Rainbow”?), etc.

    To my chagrin, he’s come out well ahead on bets this year, mainly hearing what I pick and betting precisely the opposite.