Ottoneu Arbitration Technique #1: Measure Against the Average

One of the very best aspects of Ottoneu fantasy baseball is that you are involved all year round. As October hits, stats are no longer accumulating, points are no longer being totaled and performance measurements remain locked in the past. But arbitration begins and the business side of baseball is front and center. Would you believe that someone, somewhere, in an Ottoneu points league is rostering Ronald Acuña Jr. for only $26? It’s true. If he’s not a candidate for arbitration allocation in that league, I don’t know who is. This is a pure example of why arbitration matters. If the person rostering Acuña for only $26 doesn’t have that salary adjusted, they would go into the draft with Acuña and the additional dollars to auction another big name. Oh, the humanity!

You can find all kinds of interesting situations like the Acuña one by downloading average salary data right from your league page and in this post, I’ll take you through the details on how you can use it to generate insights and strategy specifically for your league.

Step 1: Download average salaries and make it specific to your scoring format

If you click on the “Players” tab at the top of your league page, the sub-menu has a link all the way to the right titled, “Average Salaries”. You can also click here. The drop-down menu in the top right corner of the page allows you to specify salaries based on your scoring format. Choose the option that matches your league and then click “Export as .csv”.

Step 2: Merge average salary data with your league’s roster data.

If you followed Step 1 above, then you have your “average salary data”. Now, back on the “Players” tab, simply click “FanGraphs Sortable Stats”. This will take you to a FanGraphs leaderboard. Make sure the drop-down menu reads “All Teams” so that you are being given salary information for your league-mates rosters. Lastly, merge the two data sets on “Name” and subset it to “Player Name”, “Average Salary”, “Last 10”, and “$”, which represents the actual salary the player is currently rostered for in your league. Here’s an example:

You’ll notice a few things in the table above. First, I’ve also included “Last 10” which gives an average of the most recent 10 completed auctions for that player. You’ll also notice that I calculated the difference between the player’s average salary and what they are actually rostered for. From here I can start to make some decisions. For example, I’m not worried at all about the roughly $4.00 difference between the average salary and the actual salary for Benintendi and Kelenic. If you look at Benintendi’s “Last 10” you’ll notice he’s trending down anyways. By 2024, he may be worth less than the $5.00 he’s actually being paid. Yordan Alvarez, however, needs some adjusting. He’s worth more than $34, just try and change my mind.

Step 3: Group your new data set by team to determine who has the most “surplus value”

You can eyeball this process by simply going to your league’s “Arbitration” page and looking at the comparison of “Curr Salary” versus “Proj Salary” by team. Remember that you must give each team in your league at least $1. Note that this process does not provide a true “surplus” value for each team because each team is also overpaying on players. However, you won’t know who is being cut for a number of weeks, and that probably shouldn’t factor into your allocation strategy. It’s important to take stock of who in your league seems to have all the riches. There are a few different ways to do this but I like to take a simplistic route and isolate the league to players who are rostered lower than the average salary. Then, I sum the difference (Avg Salary – Actual Salary) by team and end up with something like this:

Right away I can see that there are two teams who have a big discrepancy between what they are paying and what other teams are paying on average. That could be a difference between two or three players, or it could be that a team is rostering a handful of players for a few dollars less than average. Let’s take a look at team F to see what is going on:

Team F looks a little less scary when you see that the value difference is spread out. Again, Yordan Alvarez needs to be adjusted. But, who else on this list should I allocate arbitration dollars to? Well, that’s the fun part. It’s not necessarily as easy as just tossing dollars on Yordan and Devers. Even if at the end of arbitration, Alvarez’s salary increases to $50, I’d probably still be inclined to keep him on my roster if I were the Team F manager. If that is the case, what does that actually do? Well, it limits the amount Team F will take into next year’s draft, but it doesn’t free up Alvarez for me to draft. That’s where the real strategy comes into play and over the next few weeks, our Ottoneu team will be writing more about arbitration strategy.