My last post effectively compared projection systems by how well they predicted player skill level: I scaled each projection to match 2012 actual ab/ip, but used the rates each system projected to generate stats. Tango asked if I could run the reverse, a comparison where I used prorated actual 2012 stats but kept only the playing… Continue reading Projected Playing Time Comparison
Playing-time Neutral Projection Comparison
In response to Jared Cross’s suggestion, I’ve done one more set of RotoValue comparisons of projection systems. This time, I’m taking players’ actual 2012 AB or IP, and scaling the projections from each system to match that level of playing time. Also, since commenters Rudy Gamble and mcbrown were asking for ZiPS data, I’ve included that… Continue reading Playing-time Neutral Projection Comparison
Revised Projected RotoValue Comparison
Tom Tango highlighted my previous post on comparing computed RotoValue prices from projection systems, and he and others in the comments had some good suggestions for improving the player pool. So I’ve run some more data with slightly different sets of players. First, for each league configuration, I’m simply using the top 230/240 players in the… Continue reading Revised Projected RotoValue Comparison
Comparing Projected 2012 RotoValue Prices
I’ve previously compared five MLB projection systems for batting and pitching rate statistics, comparing the projections for 2012 with actual data. This post will compare 4 systems by looking at the RotoValue prices for a given projection stat set and league setup compared with actual 2012 data for the same setup. The four systems I’m testing will… Continue reading Comparing Projected 2012 RotoValue Prices
2013 MLB Projections, Take 1
I’ve revamped the RotoValue projection algorithm for 2013, and uploaded a first cut to the RotoValue web site. Here’s the top 20 players in a 5×5 mixed league format (click on the image to see the interactive page): This model is based largely on Tom Tango’s Marcel, but for pitching I force BABIP to be… Continue reading 2013 MLB Projections, Take 1
Reviewing Pitching Projections
Last week I posted some statistical results comparing five 2012 projections systems’ statistics to actual 2012 numbers for wOBA, a good summary offensive rate statistic. Now I’d like to run a similar analysis, but using pitching data, and 3 pitching rate statistics. I’ll be running numbers for a total of 7 systems: CAIRO – from S B… Continue reading Reviewing Pitching Projections
Testing New Projection Models, and More Offensive Stats
As I’ve noted before, my older projection model has not done as well at projecting batters’ weighted on base average (wOBA) as several other publicly available systems, so I’ve been trying a different method. I’ve now tried doing something very similar to Tom Tango’s Marcel method – take a weighted average of recent performance, regress… Continue reading Testing New Projection Models, and More Offensive Stats
Reviewing Five 2012 MLB Projection Systems
Last year I ran some comparisons of a few projection systems for major league baseball, comparing several projection systems against 2011 data. So I thought it would be interesting to run a similar comparison of the five sets of projections I made visible for 2012 on RotoValue: CAIRO – from S B of the Replacement Level Yankees Weblog.… Continue reading Reviewing Five 2012 MLB Projection Systems
More "Make-it, take-it" Data
At the suggestion of Tom Tango, I ran my basketball simulator with many different inputs to see what impact different scoring levels and game lengths might have on the change to a “make-it, take-it” rule for basketball replacing alternating possessions after scoring. The short summary is that I find overtime games are much less likely… Continue reading More "Make-it, take-it" Data
"Make it, take it" Simulations
In a discussion on Tom Tango’s blog, Phil Birnbaum was speculating about whether switching basketball to “make it, take it” might change the balance of the game, and he thought it might help the underdog win more often. After reading his comment, I thought of a rather simple simulation I could hack up to test… Continue reading "Make it, take it" Simulations