Quick update on our end-of-season projections, focusing on the “In The Conversation” (ITC) metric we discussed in this pre-season blog. The aim is to anticipate which 6-7 teams will the playoff debate focus on going into the conference championships. This is all based on the sim we slaved over in August, updated for what we’ve…
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It’s been a slow start thus far this year, with our official plays going 1-1, while both of our leans lost. That puts us at 1-3 on the year, but it is early days still. Here are this week’s picks: Big Plays (0-2 YTD) Chicago +7/+7.5 at Dallas [M-P Line: CHI +3.1] Other Plays (1-1…
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Here are our “grades” for the third week of the college season. We control for game location and opponent quality, and discount garbage time situations. score diff is how we’d expect the team to do against an average team on a neutral field based on the way they actually played in the game, but using only predictive metrics. pctile rating is a rating of…
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Here are our “grades” for NFL Week 2. We control for game location and opponent quality, and discount garbage time situations. exp score diff is how we’d expect the team to do against an average team on a neutral field based on the way they actually played in the game, but using only predictive metrics. pctile rating is a rating of the team’s performance,…
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Here are our “grades” for NFL Week 1. We control for game location and opponent quality, and discount garbage time situations. exp score diff is how we’d expect the team to do against an average team on a neutral field based on the way they actually played in the game, but using only predictive metrics. So Pittsburgh was fundamentally 10.7 points better than an…
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Here are our “grades” for the second week of the college season. We control for game location and opponent quality, and discount garbage time situations. score diff is how we’d expect the team to do against an average team on a neutral field based on the way they actually played in the game, but using only predictive metrics. So…
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The season got off to a sluggish start, with both our official plays losing, though our one lean was victorious. As I mentioned last week, we’re weighting the market number more heavily early in the season, so the threshold for something to quality as a pick is a little higher than in the past. I…
DetailsTeam can play well and lose, or poorly and win. In order to see beyond the score to determine how a team performed fundamentally, we score a team’s performance in each game relative to all games played in the last ten years, accounting for opponent strength. With this tool we can objectively see which wins were…
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Welcome back! It’s been a long offseason, but during that time Cade and I have made some improvements on our model(s). We’ve also examined its historical performance more closely and critically, and found that our predictive value, relative to the market, increases as the season progresses. To folks who know the basics of our methodology, this shouldn’t…
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Rufus and I always enjoy the NFL post-season projections we update throughout the season. Frankly it might be our favorite product. This year we decided to put together something similar on the college side. But since the playoff committee lies beyond a humble quant’s domain, we have to approach it a little differently. Our projections…
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