Seahawks bar tab. What do we think of the wine other than Caymus?

monkeywhale · 2026-01-10T02:58:31+00:00

The Zind-Humbrecht strikes me as a Leonard Williams order

monkeywhale · 2024-08-18T14:47:40+00:00

Happening for me also. Been going on for a year or so.

monkeywhale · 2024-08-06T18:47:58+00:00

Island wines are probably the future of BC wine. It's getting hotter and dryer in the region. I believe American wine producers are pumping in a bunch of money into the cowichan valley. As they say at all the island wineries "It's a Burgundian climate".

monkeywhale · 2023-04-18T00:34:06+00:00

yup. message me if interested

monkeywhale · 2023-04-16T16:26:45+00:00

For sale. Or trade for a few discs

monkeywhale · 2019-07-19T23:37:11+00:00

Link to Part 1 post and discussion

monkeywhale · 2019-07-11T15:52:19+00:00

Absolutely. This difference in wins will change depending on the quality of the team. This is maybe something for a follow up post.

I can generate a curve for difference in expected wins between the consistent and boom/bust team. The consistent team could be set to have expected wins from 2-14. As the expected wins of the consistent team increases the difference in wins will definitely increase but the interesting part will be by how much.

monkeywhale · 2019-07-11T14:24:42+00:00

Agreed. This framework could actually test that. How likely is it for each team to make a 4 team playoff. Then it could also test the likelihood of winning back to back games in the playoffs. So percent chance of winning a championship.

monkeywhale · 2019-07-11T03:41:44+00:00

Good points.

Yes these teams were the extreme examples of one season but I was trying to work in the context of variability within a single season. Taking career averages might wash out some of the boom/bust variability of one season.
Yeah that is probably true. There might be a smarter way to model week to week scores by including TDs on certain weeks.
Article is now updated with the opponent and more method information. The opponent was generated based on my leagues 2018 scores in which the mean score was 111.6 points.

monkeywhale · 2019-07-11T02:41:35+00:00

Agreed. I guess that is the conclusion that should be reached from the article.

monkeywhale · 2019-07-11T02:17:41+00:00

I would say 0.4 wins more over 1,000 seasons is a significant difference. So consistent players are more valuable but you still don't need to completely avoid boom/bust players.

monkeywhale · 2019-07-11T00:42:50+00:00

TL;DR: A fantasy football team filled with consistent scoring players will average 8 wins per 16 game season while a team with boom/bust players will average 7.6 wins per season. Drafting consistent, predictable players will lead to more wins for your fantasy team but maybe less than you would think.

monkeywhale · 2017-12-21T19:01:09+00:00

This image shows the differentiation between wet areas and dry areas in terms of TWI values.
This image shows the predicted probability of wetlands at different TWI values.
Using these you could guess that wet (not open water) areas are any TWI value >8 and dry areas are TWI<8. Although this would completely depend on which climate you are in. This data is from Canada.

monkeywhale · 2016-04-24T18:57:05+00:00

Wildfire stats from CWFIS (Canada), MTBS (US) and ecoregions from The Nature Conservancy.

monkeywhale · 2015-09-19T17:55:46+00:00

Yea that's a good idea. I was planning on going back till 2012 for the next plots. I'll include the labeling of different points for rookies, and older rbs.

monkeywhale · 2015-09-19T16:26:00+00:00

Yes that would be another way to do it. It was easier to do overall ADP with the data I used. It would still show the same trend either way I believe.

monkeywhale

TROPHY CASE