It has come to this. In every sport it’s possible to find predictions, whether in the Las Vegas sports books or in your weekly fantasy league. But what if you could have a slight advantage over the rest of your league mates? What if you could predict the future?
Well, you’re looking in the wrong place! This article is basically just a proof of concept from my last article in that I am going to make some minor tweaks to the 40-30-20-10 Rule to see if they can predict the outcome of a tournament more effectively than The Golf Channel‘s WinZone.
This Week’s Field
From the looks of the PODS Championship field this week, it doesn’t appear to be a very exciting tournament. Most of the big names are taking some time off for practice. However, there are a few tournament winners in the bunch with Vijay Singh (#9) being the low World Golf Ranking golfer in the field with Sergio Garcia (#13) next in line.
The field does have six 2007 tournament winners. This is a point of interest in my revised formula as I believe a player that has won already in the current year has shown they have the game to win.
My Revised Formula
If you are unfamiliar with the 40-30-20-10 Rule, please first read up on it… the abbreviations will make more sense that way:
(0.4 GIR) + (0.3 P) + (0.2 DD) + (0.1 DA)
-----------------------------------------
(WINS * 0.05) + 1
This is essentially Dave’s 40-30-20-10 rule, with one change: the divisor. I added a divisor to account for wins in this year’s tournaments.
The Predictions
I know our readers have said it’s not possible to make meaningful guesses based solely on statistics, and I completely agree with you. However, for the sake of this article I would at least like to take a stab at predicting the outcome. Here are my predictions for the tournament finish:
Pos Player My Rank 40-30-20-10 Rank --- ------ ------- ---------------- 1 Charles Howell III 32.5 * 34.1 2 Vaughn Taylor 38.9 38.9 3 Vijay Singh 40.3 * 42.3 4 Charles Warren 45.1 45.1 5 Jeff Quinney 46.6 46.6 6 Ted Purdy 47.7 47.7 7 Nick Watney 48.4 48.4 8 Bubba Watson 51.0 51.0 9 J.B. Holmes 51.1 51.1 10 Stephen Ames 51.3 51.3 * 2007 Tournament Winner
It is interesting to note that only two of the six winners from this year are in the top ten in my list. Could this prove they just had a lucky/good week? Possibly, but I also see two of this years winners in the top three of my predictions. It just so happens that Vijay is also on my fantasy roster for this week!
Let’s take a look at how the rest of this year’s winners finished up using my new formula:
Pos Player My Rank 40-30-20-10 Rank --- ------ ------- ---------------- 16 Mark Wilson 53.2 55.9 17 Charley Hoffman 53.3 56.0 19 Paul Goydos 56.1 59.0 38 Fred Funk 71.0 74.5
Now you may have noticed something here. A little earlier I had said Vijay and Sergio were the two highest ranked players in the field, but Sergio is nowhere to be found in my predictions. Why? He hasn’t played much golf on the PGA Tour, so adding the weight of his statistics would be frivolous. He falls wherever he falls, but on a week-to-week basis. His rank, by the way, in both systems is 90.9 (0.4 * 169 + 0.3 * 10 + 0.2 * 11 + 0.1 * 181).
The Debate
Sure anyone can come up with a method to predict the outcome of a sporting event, but how truly accurate can it really be? As stated in some comments in the previous article, golf has too many individual player variables to really have any type of chance of predicting any outcome. On top of that, there are 143 players in the field that could realistically win this tournament. Sure, some of them may be playing hurt or not in the right mental state, but they are still in the field and still have a shot at the title.
Take this for what it is, and for what it isn’t. It is just a humble IT professional’s measly efforts at trying to come up with an easy-to-use formula based upon Dave’s 40-30-20-10 Rule to predict the outcome of a tournament. I am about 90% certain that my top ten will be lucky to be 10% correct.
With that, I open this article up to comments. What could be changed or added to my new formula to help predict the outcome of a tournament? Do we factor in the weather and course conditions? Do we calculate if a player is on a “hot” streak? What about if they have won on the course the tournament is being played at? Let your mind run wild, and then let me know what you think!
This article was written by guest author Harry Solomon, an active member of our forum.
Dividing someone’s total by 1.05 or even 1.1 isn’t going to do much. Either someone had a good week and dividing by 1.05 is only going to pull their sorry 124.3 ranking to 118.4 (big whoop) or they’re having such a great year (think Tiger Woods most any year, Phil Mickelson, Vijay Singh in 2004, etc.) that their score is already going to be low without the division by 1.25. Plus, this early in the year, forget it. We’ve not played enough tournaments to have very accurate rankings. A one-week hot streak dramatically shifts the rankings.
Of course, that’s assuming you’re remotely correct in how you’ve chosen to apply the formula. Dave’s 40-30-20-10 rule was calculated after an event to show the relative weight of a few common statistics (GIR, PA, DD, DA) on a week-to-week basis. Dave then applied the rule to entire seasons and got even better results (for obvious reasons).
You’ve applied it backwards. While Dave used it as an analytical tool (after the fact), you’ve tried to cram it into the mold of a predictive tool. If golfers were consistent, that might actually work. They’re not.
Well, now that you’ve gone to the trouble of actually making the predictions, it’ll be at least mildly interesting to see what happens. I would be shocked to see some of those guys finish in the top ten. 🙂
You know, if you could factor in the course attributes, like length, fairway width, green size, whether the rough is penal or not, etc, that might be interesting to look at. I’ll bet it would affect your predictions.
What would really be cool is if you could apply the course attributes to an entire season of stats, to see how much a particular course-type affected various types of players. If that worked out, it could lead to a tool that course designers might use.
I kind of have to agree with Erik that this seems a bit of a stretch. Should be interesting though, to see how close your predictions come to the final outcome.
The waxing and waning of a pro’s performance week to week seems to me to be statistically confounding. That’s one of the reasons I’m not sure season wins is an appropriate component of any predictive formula.
Had I the brains or time to try to come up with a predictor I would probably want to factor past performance at the specific golf course in question along with performance in the last one or two events.
Of course, were any method possible, it would have been discovered by now and nobody in Vegas would be making book on golf tournaments! 😛
Can you do this for every tourney so I can us it for the golf challenge I participate in? Thanks!
And good for you: starting next week, The Numbers Game will run on Tuesdays, not Thursdays. So it could work. But c’mon, the formula is easy enough. Go ahead and run it yourself, Lazy Bones. 😀
One suggestion to the formula would be to adjust the player’s ratings for how they have performed at that particular course over the years.
You could take their season’s stats (last 52 weeks would be better than just last 2 months) as 50% of their number + last 5 years playing at that course as another 50% of the numerator and then apply your divisor to see what the predictions would be.
I would bet KJ Choi would move further up as an example, because he has done well at Tampa.
I made these factors up on the fly, but you can analyze this to calc a better number.
I think Vegas odds are usually meaner than they should be for most players. I picked Furyk to win the US Open a few years ago when he did, and it only paid out 30 to 1. In hindsight, it was a good bet, but I would bet that people aren’t making a living on golf bets, except when Tiger gets going on a roll.
Will The Numbers Game 40-30-20-10 rule data be available for the WGC-CA this week at Doral? If so, can you please direct me to the web location or link? I would do it myself but I don’t know how to automatically get the data for all players in the field. I would love to apply this formula to my draft in the WGC. Let me know. Thanks!