I wrote a post back in May about the MLB negotiations, trying to understand the perspectives of both sides by applying what I learned from a class I took in the spring called "Negotiation and Conflict Resolution." Negotiations will always require human interaction and I am not trying to reduce that. What I am trying to do is think about ways in which negotiation strategies could be automated in order to make better decisions faster, with less subjectivity and overall just a cool visual to have at your disposal.
This is pretty useless in the public realm, but inside an MLB organization or agency, I do think this could be valuable even though it relies largely on common sense. For the sake of this post, I created a database of all the 2021 free agents with three values: 2021 ZiPS Projected WAR, 2021 Steamer Projected WAR, and their 2020 season WAR over a 162 game season. Those values were then converted to arbitrary dollar per WAR values in order to get 2021 price points for each side of the negotiation. The lowest of the dollar figures was renamed "Resistance" for players and "Target" for teams, with the same thinking in mind for the other price points. I gave players and agents a higher dollar per WAR ask because, well, they should always be seeking the highest possible amount they can justify. But like I said, the values are arbitrary and would be much more useful if internal figures were used.
Above is what would be considered a negotiation with a "Negative Acceptance Zone" from a team's perspective because their intention point is lower than the player's intention point. The green-shaded area is essentially where both sides will find satisfaction with a deal. The blue-shaded areas are known as the " Positive Bargaining Zones." The acceptance zone is included in the bargaining zone, and it is the area between either sides' resistance points. A deal can be struck within the bargaining zone, it is just less optimal for one side. A "Negative Acceptance Zone" is not necessarily a bad thing, it just likely means negotiations will drag on longer than if there were a "Positive Acceptance Zone," which looks like...
The above example is a "Positive Acceptance Zone" because the team's intention point is higher than the player's. This is more rare because it's hard to think of a scenario where a team's intention point is higher than a player's. Both sides would be happy with something with an average-annual value (AAV) between $3.24 million and $4.05 million, and would likely accept something between $2.4M and $5M (without taking other offers into consideration).
This is an example of a scenario where a team's intention point is lower than a player's resistance point. There is still a green-shaded area, so both sides can find something they like, but there is just less room to work something out.
This is an example of a deal that will...not end in a deal because the red area is what is called the "Negative Bargaining Zone." A deal will not be made in this situation because it falls outside both sides' resistance points. That is, as long as neither side breaks their commitment to their resistance point.
Use Cases
Everything is a negotiation. Free agents, potential draft picks, arbitration-eligible players and trades come to mind first. With a more accurate measure of how teams value players ($ per WAR on log scale, or similar), this becomes more interesting. Combine that with historic tendencies of how agents value players and this gets even more interesting. While it may not be groundbreaking stuff to see how different points look on a spectrum, it could give either side insight into where they can expect to get a deal done, and focus elsewhere if they do not see any area to get a deal done.
I touched on it briefly, but having a profile on how different agencies value players would be valuable, in addition to grading out their temperaments. What I mean by that is what they are like at the negotiation "table." This information would give teams the ability to put together negotiation alternatives based on a specific agents' temperament, track record in say the arbitration room, and expected values for every alternative. Below is the hypothetical chart I created for my post back in May, but could be automated for a specific agent with enough information.
This type of decision-making map could be particularly useful leading up to the non-tender deadline and determining whether or not you should go to an arbitration hearing. Maybe instead of using WAR projections, the price points are determined by low-end, mid-tier, and upper-end player comps.
Overall this may not be a huge value-add, but I do think it would be useful to visualize how a negotiation could go and help stick to a strategy.
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