Background

Trades

Players

Imagine you’re the GM of your favorite team. Ever wonder, “What would it take to get [player x]?” if your team needs to fill a gap? Or, “What can we get for [player x]?” if your team is underperforming? Did anyone ever answer that question to your satisfaction? Maybe it was on a website, or in a chat, or on a radio show? We’re guessing the answer is… no.

And we think that’s because there’s a gap here. Fans don’t really understand how teams value their players. Heck, most journalists don’t either. If they answer, they’re probably just guessing.

Well, we’re here to answer those questions, and then some. We built a database with estimated trade values of over 2,700 players – from established major leaguers to obscure prospects – so you can get a better sense of what those players might be worth in trade.

Are we making this up?

No. We studied hundreds of real-life trades, and used those as a guide to match up our numbers to the ones MLB teams are using. Check out our History section to show how our values match up to theirs.

Are we experts?

No. Well, maybe. No, we’re not professional baseball front-office analysts, so we have no official license for this, if there is such a thing. But okay, maybe we know what we’re talking about, because we’ve been doing this for some time as a hobby. We’re serious baseball fans who have written quite a bit for fan sites on this topic. We also have some skills at statistical analysis (we’ve worked in Finance, have MBAs), and we thought we’d apply them to trade valuation to build (what we hope is) a model that correlates well to real life. We’ve fine-tuned and adjusted our numbers along the way, and decided to go public with our approach once we got the system to be reasonably accurate.

This site has also been featured in the media, including the NY Daily News, ESPN NY Radio, The Ringer, and Fangraphs’ Effectively Wild podcast.

Will our numbers be right all the time?

No, because that would be impossible, because team needs are different and in-house models vary. And it’s important to note that we are not trying to be predictive. But we do think they are reasonable estimates — reasonable enough for fans to enjoy using them as a basis for our popular Trade Simulator. We are also transparent about how our numbers match real life.

How do we know teams are using numbers like ours?

We don’t. Front offices have invested in valuation departments and sophisticated analytical engines much bigger than ours. But we think we’re on the right track. We have enough evidence to suggest they’re using models. Even super agent Scott Boras acknowledged it, in an April 2019 story in The Athletic by Ken Rosenthal (by way of criticism of it):

To hear Boras tell it, the problem is not his negotiating style, but the way that clubs use analytics to value players, often landing at similar dollar amounts in their appraisals.

“These markets are very different because we have got a dynamic where the valuation component is common to all teams by design,” Boras says.

In our view, Boras is confirming what we already suspected and observed: that teams are using similar analytical models to value players.