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Jim Furtado
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Tuesday, July 11, 2017

The Recent History of Free-Agent Pricing

But first this piece will explain how I actually calculate average value — the reference point for whether players are undervalued or overvalued. It is also the appropriate reference point when considering the opportunity cost of any other number of baseball moves. For example, when a team is considering the value of acquiring a young player who will produce a large volume of team-controlled WAR, the reference point for valuing him is the cost of acquiring that amount of WAR on the free-agent market. This is an important concept for team construction….

While the last few years have clearly seen growth in Dollars per WAR in excess of that rate, I believe that this was largely a function of the declining WAR share of players with six years of service time. I’m skeptical that such a development can continue indefinitely, and I think that, as the WAR share of such players flattens and salaries grow continuously, we should expect salaries to grow at about this 5.9% rate. After all, free-agent spending net of the league minimum only grew 5% per year since 2006, with the remaining growth in Dollars per WAR coming from the shrinking WAR in the denominator.

RoyalsRetro (AG#1F) Posted: July 11, 2017 at 05:15 PM | 1 comment(s)
  Beats: war

Wednesday, April 12, 2017

Stats All, Folks: WAR, what it is, what it’s good for and the absolute best WAR Orioles - BaltimoreBaseball.com

fWAR and bWAR, it’s no wonder people get confused.

Jim Furtado Posted: April 12, 2017 at 08:46 AM | 56 comment(s)
  Beats: orioles, sabermetrics, war

Monday, March 06, 2017

Statcast and the Future of WAR | FanGraphs Baseball

I’ve argued about this for 20 years. The MVP question and the best player question are two entirely different things. Using WAR for either conflates the two. Why not transform WAR into a purely contextual answer (value) and continue to define results in runs and wins based on outcome and then use Statcast probabilities as a scouting tool for the best player question? In my mind, using Statcast as the inputs on an improved 20/80 scouting scale and apportioning all the components properly would be a wonderful upgrade to what’s done now. It would also put teams on a better path for projections as they will be able to better quantify aging patterns in a more realistic way.

This tension between what happened, how it affected the scoreboard, and how much credit to give to players for things they don’t control is a difficult thing to resolve. And now that we’re getting even more granular metrics about a player’s contribution to outcomes, these questions are going to continue to be relevant. Knowing the guys at MLBAM on a personal level, I’m pretty comfortable with the fact that they’ll handle these questions thoughtfully, and if (or when?) they do produce an MLB.com WAR model, it will be with all of these questions answered as well as they feel they can.

But while Statcast holds a lot of promise for improving the pitching and defensive sides of the components, getting ever-more granular hitting data might force us to again ask what we want WAR to be, and what the goal of the model is. There is no obvious right answer here, and that’s one of the reasons there will always be multiple ways of calculating WAR.

Jim Furtado Posted: March 06, 2017 at 01:48 PM | 5 comment(s)
  Beats: statcast, war

Mike Gimbel’s video of RPA vs. WAR plus 2017 predictions.

Mike Gimbel’s video was made on February 28th. It contains criticism of the WAR formula(s), using a comparison of results from the 2016 season and an analysis of all 30 MLB teams going into the 2017 season.

caiman Posted: March 06, 2017 at 09:49 AM | 8 comment(s)
  Beats: mlb, rpa, sabermetrics, war

 

 

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