Beatpaths

I messed up a bit on the previous bit of backtesting, although the way I messed up was informative. The previous round of backtesting tested the beatflukes variant (not vanilla), and each year had all the game results of the previous seasons in my dataset. So, 2006’s results was using a beatpath graph based off [...]

I’ve managed to fire up my old wonky backtesting system. It doesn’t have a lot of ability yet, but it gives some interesting information. Here’s what I’ve found.

Year
Random
uNet
Prev. Week
Beatloop Str.
Fractional
BPower/Win/Loop
Str. of Beatwins
Bucklin
UPower
UPower/Loop
UNet-Lookahead

2004 (84-57)
150-117
166-101
157-110
160-107
164-103
167-100
166-101
161-106
164-103
161-106
157-110

2005 (91-45)
162-105
152-115
152-115
162-105
156-111
160-107
151-116
156-111
156-111
157-110
152-115

2006 (94-52)
156-111
163-104
159-108
161-106
163-104
167-100
164-103
164-103
163-104
161-106
159-108

2007 (89-43)
162-105
164-103
169-98
162-105
165-102
167-100
158-109
166-101
165-102
171-96
169-98

2008 (80-48)
158-108
159-107
160-106
156-110
163-103
159-107
160-106
160-106
163-103
161-105
160-106

TOTAL: 64.13%
59.03%
60.22%
59.70%
60.00%
60.75%
61.42%
59.85%
60.45%
60.75%
60.75%
59.70%

So, there’s some food for thought. Here’s how to read it – the records in parentheses are the [...]

Here’s a review of Isaacson-Tarbell, which we should compare our picking schemes against this season.
Isaacson-Tarbell is “picking for idiots”. And it’s pretty bulletproof – it seems most pick experts can’t outperform it. The picking rules are: Pick the team with the better win-loss record. If they’re tied, pick the home team.
Isaacson-Tarbell was 9-7 for week [...]

I thought I’d take the opportunity to trace through the general strategy here, both to get my brain clearer for the season, but also to review for whoever is reading.
We start out with all the wins and losses for the season so far. The first design choice I made was to ignore points, and any [...]

Here’s a different beatpath graph for end of the 2008 season.
I’m surprised at how clear this looks. This is based off of my brainstorming post last week and the ensuing discussion. What I did for this graph is I simply excluded all matches this season that were intra-conference or inter-conference seeding [...]

Zooming out as I’m apt to do, another quick/reminder exploration of the various algorithms. This is restricted entirely to the graph methods.
The goal here has always been to create a pecking order of the teams, based off of wins and losses and nothing else. This means a DAG – a directed acyclic graph. [...]

As part of the upcoming redesign for Beatpaths, I’m looking for people who might be interested in posting commentary on the actual front page of the site, as opposed to simply leaving comments. We’ve had a fair amount of interest here from people suggesting new methods, ways to rank the confidence of picks, etc. [...]

Discussion on different methods are ramping up – I’d like to make one suggestion on nomenclature.
Graph Method: Methods that have to do with determining what teams have beatpaths and beatwins to other teams. Examples are the current Standard graph method on this site, the Iterative graph method, and the Beatflukes graph method.
Power Method: Methods [...]

Miscellaneous observations:
Last week’s power rankings are 10-5 9-6 so far this week.
The only two teams with beatpaths to every other team in their division: Denver and Arizona.
#31 beat #1, with some awesome direct snap misdirection.
And it’s time to start thinking of tiebreaker and rank strategies.
There are two stages to determining rankings. First is the [...]

For those that are new visitors this year, here’s a quick description of what we’re all about.
A few years back, I was reading one of those websites that purports to power-rank sports teams based off of every single in-game stat in the book. And, being a Broncos homer, I was peeved that the Broncos [...]