This is very exciting news, though the results are far from official.
As I’ve mentioned in this spot previously, I’m participating in Tom Tango’s Forecasters Challenge, which has 22 forecasters and projection systems playing out 1,000 runs of the season using teams of preranked players. I gave a rundown of what my teams looked like back in June.
I had just about given up on seeing an in-season update of how things were progressing, but Tom had the following to say Wednesday:
If the season were to end today, it would be a 2-man race between Rotoworld and John Eric Hanson. Together, they have 542 wins out of 1000 drafts! The other 20 combine to win less than these two. What a thrashing!
Many of the big names are taking part, so it’d be quite a thrill to come in first or even second. Looking at his draft run, I think Mr. Hanson may well have the edge, as the key players he’s relying on seem to be healthy and producing. It’s remarkable just how similar his rankings were to mine in some cases. We battled on many of the same players over the course of the 1,000 drafts.
Player – My team – Hanson – Total
Carlos Silva – 667 – 333 – 1,000
Brad Penny – 435 – 565 – 1,000
Brandon McCarthy – 311 – 689 – 1,000
Glen Perkins – 341 – 659 – 1,000
Pedro Martinez – 108 – 892 – 1,000
Tom Glavine – 16 – 984 – 1,000
Hank Blalock – 9 – 991 – 1,000
Brian Bannister – 1 – 999 – 1,000
Justin Upton – 630 – 368 – 998
Ian Snell – 513 – 465 – 978
Rick Ankiel – 387 – 582 – 969
Anibal Sanchez – 372 – 594 – 966
J.A. Happ – 263 – 700 – 963
Billy Butler – 210 – 711 – 921
Coco Crisp – 648 – 219 – 867
Tom Gorzelanny – 131 – 730 – 861
Robinson Cano – 50 – 766 – 816
Adam Jones – 522 – 234 – 756
Jorge De La Rosa – 76 – 658 – 734
Todd Helton – 430 – 225 – 655
Nick Markakis – 498 – 110 – 608
Alexei Ramirez – 84 – 462 – 546
B.J. Upton – 301 – 229 – 530
Carl Crawford – 346 – 96 – 442
With 22 teams drafting 25 players apiece, there’s no way we could have gone head to head like that so often strictly as a coincidence. All of those similarities are likely arising because Mr. Hanson borrowed from my playing time projections to complement his performance projections. Computers are a lot better at projecting OPS than at-bats, so those systems tend to use a mix of non-computer projections to account for playing time. That’s perfectly fine with me, if that’s all it is. Finishing first and having a hand in No. 2’s success would be pretty sweet.