By Brian Mills

In my previous posts, I addressed the topic of analyzing trades in  H2H league. I took a closer look at these trades by running simulations of weekly player totals in an attempt to ferret out how acquiring talent increases the probability of adding wins in a scoring period. I took a look at HRs and SBs.

Time now to follow up with a look at Saves.

Now that we’re nearing the trade deadline, owners are scrambling for trades that may push them over the top and into the playoffs.  One of the easier trades to get done (at least in my experience) is moving a closer to or from your team.  This is especially true in keeper leagues, where owners who “dump” likely don’t see most closers as being keeper candidates.  But what will adding Joakim Soria or Jonathan Broxton really do to your bottom line of wins going into the playoffs?  Let’s find out.

First, it’s important to note that the full season and partial season Save leaders can vary a lot.  Last year, Carlos Marmol managed 11 of his 15 Saves from August 23rd to September 23rd.  There’s a degree of fickleness involved.

For this reason, I tried my best to only include players who accrued Saves for the entire season.  I simulate in the same way I did in my previous posts (check the links at the bottom if you haven’t already).  That means that players who were part-time closers at certain parts throughout the season make up the lowest-level group.

So given this distribution, how often would we expect each group to outperform another in a given week?

By just pitting each group against one another (independent of the team variance), we would expect a 2009 Mariano Rivera type to outperform a 2009 Matt Lindstrom about 70% of the time. Of the other 30% in that matchup, 19.5% are ties, and Lindstrom wins outright only 10.5% of the time.

In the first graph here, we see the smoothed distribution of weekly totals for each group. The y-axis is the percentage of weeks that a certain total is expected, while the x-axis represents the number of Saves in a given week. The dashed vertical lines are the average Saves per week for each group of closers. But these distributions alone aren’t enough to understand how adding a closer to your team affects your chances of gaining some wins.

Adding Saves to Team Totals

Obviously, the above is a bit abstract, but less so than for the other categories.

In the actual H2H Fantasy match-ups, each closer is introduced to team-wide variance due to other player contributions.  This is a key aspect of understanding how adding Saves to your team at the deadline will affect the outcome of the season.  For now, we’ll only focus on Saves, rather than K’s, ERA, and WHIP, though it’s important to remember that closers and other relievers can contribute in this area as well.

Let’s take a look at the Saves standings in the same league I had used for my other two posts on this topic.  The averages each week look like this:

The Saves categories yields big differences from top to bottom of the standings as some teams decide to punt the category.  Or maybe they were rostering closers who turned in disappointing returns. This, we will see later, has an extreme effect across teams as to the advantages of adding closers via trade.

There are, of course, a limited pool of pitchers who actually get Saves during the course of a season.  Therefore, we’d expect that the marginal Save may be more valuable than the marginal Run or RBI.  In the second graph, take a look at the above table in graphical form for the Top Team, Bottom Team, and the Average of the other 8 teams in the league.

As you can see, there’s a much larger difference between the Top Team and that owner’s huge Saves edge, and the Average and Bottom Teams, where the difference in overall Saves is much smaller.  Let’s assume we’re making a drastic improvement in closers, going from 2009 Matt Lindstrom to 2009 Jonathan Broxton. Below is the distribution shift for each team doing a full upgrade from a 15 Save Guy to 44-48 Save Guy (from the Red to the Green distribution):

Obviously, adding closers just adds an extra save or two for a team in a given scoring period.  However, the point of this article is to understand the full advantage of adding in certain categories, hopefully culminating in an overall H2H value that accounts for the extreme variability in short weekly sessions.  So, just like the above, I simulated each level of team against one another (Bottom, Average, Top) in order to gauge the expected win increase by upgrading.  I won’t include the full tables here, but they can be had upon request.

Below I have smoothed out the expected win increase for each team by the number of Saves added for each upgrade.

Again, the first thing that pops out is the enormous difference between the Bottom/Average teams adding a Closer, and the Saves leader adding a closer.  Because the Top team in this league already had such an enormous lead, adding a closer does very little to the expected Wins for Saves over even the full 26-week scoring period.

The bar chart further shows the huge difference in Saves needed to gain an additional win.  If the Top Team were to add Andrew Bailey at the beginning of the 2009 season, that owner would only be expected to gain one additional Category Win over the course of the entire year (including playoffs).  While Bailey came cheap, trading for a player with 25-30 Saves doesn’t seem like a good investment for the owner who already owns Rivera, K-Rod, Nathan, and Broxton.

But take a look at the other owners.

Since there was such a dominating team in this league sucking up all the Saves, other teams would be gaining about 5 or 6 Wins over the course of the season by adding Andrew Bailey from waivers early on (ignoring the net effect of whoever Bailey replaced).  That’s pretty considerable.

And because the Saves are so wrapped up in a single team, if you were to trade for a solid closer here at the deadline from that team, then the effect may be even greater depending on the match-ups for the rest of the season.  Why?  Because you are both increasing your total and decreasing that other owner’s, enhancing the net effect.  Be sure to note that the graph depends on the time of season that a trade is made.  An extra 20 saves from the midpoint of the season should net you about half what the graph says.  Just pro-rate things based on a 26-week season and you should get a solid estimate.

So what can we learn from this?

Well, if you only have one closer on your H2H team in a 10 or 12-team league, they’re likely not helping you with much.  You have one of two options: 1) Trade that closer to upgrade your hitting elsewhere (see our other articles on HR and SB upgrades) or 2) Get another closer if you can.

An additional 20 Saves over half a season results in about 2 or 3 additional wins.  Depending on the type of league you’re in, it may be relatively easy to pry away a closer from someone: especially if it’s a keeper league and owners are dumping.  If you’re at the bottom of the barrel with a single closer, adding Mariano Rivera or Jon Papelbon from a dumping team could net you about 2 category wins from now through the playoffs.

Or perhaps you are that top team and are short somewhere else.  It may not hurt too much to get rid of about 15-20 Saves for the rest of the season to gain in other categories.  If you’re in a competitive league, that could make a difference.  But always remember the net impacts of your trade in all categories, as well as the increases other teams would expect from trading with you.  Hopefully with more knowledge about the expectations of deadline trades, you can weasel out some extra value that your competitors have overlooked thus far.

Previously:

Trading for Power in H2H Leagues

Trading for Speed in H2H Leagues