Do you remember the first time you discovered that short division produced the same results as long division? That resounding, definitive "Aha!" moment, the certainty that yes, clearly, you were destined to a greatness usually reserved for the likes of Euclid or Newton or, dare say it, Fibonacci?
Do you? Anyone? Oh, well, maybe that was just me.
That feeling came back to me as I crunched the numbers for my regular bizarre but statistically fueled prediction of who will win the next major. Days were spent poring over numbers of indeterminate importance and names of even less value (although, for what it's worth, I believe the combined world rankings of Open Championship participants Rhys Enoch, Chris Rodgers, Juvic Pagunsan and 2003 Open champ Ben Curtis equates to a Fibonacci number).
My point is this: Sometimes the answer you're looking for can be arrived at by a much more concise method. (This, I've come to understand, also can applied to one's short game, as well as cleaning out your email inbox.)
But I digress.
Based on a careful review of the meaningful statistical categories and some computational gymnastics that might cause Stephen Hawking to sprain a neuron, the winner of the Open Championship will be Adam Scott. The case can be made, of course, that to arrive at such a decision would have been far less taxing had I merely consulted the top of the table of current Official World Golf Rankings. You could do that, but as anybody who's seen me mulling toothpaste choices at the grocery store knows, I tend to want to make things more complicated than they need to be.
Fact is, though, that as much sense as Scott makes in the abstract, he makes even more sense in the concrete block-headed-ness of my methodology. Now, if you'll recall, I have not been particularly successful in choosing major champions based on statistics. Zero for three, as a matter of fact. To review, I first chose Boo Weekley for the 2013 U.S. Open. He missed the cut. Then I (and my numbers) outlandishly chose Jordan Spieth for this year's Masters. I was close, as he actually had the lead in the fourth round, but faded to a T-2 finish. At this year's U.S. Open, the numbers and I went off the reservation again and chose Bill Haas. Apparently my calculator (the trusty TI-30, thank you very much) was drunk as Haas finished T-35.
Quite honestly, none of those choices made much sense, but this one does. Suffice it to say, Scott displays the characteristics that are a fine blend of the Open winners of the last decade. Here's an overview of the seven criteria I considered:
From all that data, I concocted a statistical stroganoff (or better, a Shepherd's Pie) that seems ludicrous until you find that the names it spits out make more and more sense. I could explain my method, of course, but then I would have to kill you. In simple terms, each of the seven criteria (age, world ranking, wins, driving distance, driving accuracy, greens in regulation and putting) were converted to a 300-point scale. Why 300? Well, I like the movie, but from a statistics standpoint it lines up well with driving distance and lets values like world ranking and putting (where lower scores are better than higher scores) match up more consistently with the other statistical areas.
Confused yet? Good.
Now, the average score across those seven criteria for the Open Championship winners of the last decade was 2,060. My theory was that the current player in the field whose numbers added up to as close to 2,060 as possible would have to be my pick to win the Open this year.
Graeme McDowell (1,920), Sergio Garcia (2,035), Luke Donald (1,910), Martin Kaymer (1,910), Thomas Bjorn (1,991), Jim Furyk (2,084), Zach Johnson (1,999), Henrik Stenson (2,012), Ian Poulter (1,909) and even Miguel Angel Jimenez (2,162) were all in the vicinity of the magical number of 2,060.
But Scott matched the number exactly. Exact. Ly. Even a statistician can't ignore that kind of coincidence.
Especially when it's so obvious. Surely, Fibonacci would be proud.