With this in mind, our “Trend of the Day” series features articles that walk subscribers through an important trend each weekday, created by our Trends tool.

MLB Trend of the Day: Low-Priced Outfielders Who Excel — But Maybe Not Right Now

If you go into our Player Models and look to build a lineup for the 7:05 PM ET slate on DraftKings, you’ll see a lot of outfielders — which makes sense, as every MLB team starts three of them and there are 18 teams playing in the slate. Because of the sheer number of outfielders available and the DK requirement that you start three, sorting through them to find players you like might be laborious, especially if you have paid up at other positions and are now looking for productive outfielders who aren’t expensive.

So let’s see if we can find some decent outfielders on the cheap.

Step 1: Player Filters > Position > “OF”

Step 2: Player Filters > Salary > “2,000 to 3,500”

So these outfielders, despite being relatively cheap, actually aren’t horrible. They seem unlikely to destroy your lineup. But we can probably do better.

What if we focus on batters hitting near the top of the order so that we can screen for only those batters who historically do well?

Step 3: Player Filters > Lineup Order > “1 to 7”

Hang on, what’s this? Whereas the average batter in the bottom half of the order has a negative Plus/Minus, in this cohort of cheap outfielders, the sixth and seventh batters amazingly tend to exceed their salary-adjusted expectations. For some reason, this trend has matched for some batters who might provide hidden value and thus enable users to create unique lineups in tournaments. Not too shabby.

Let’s not forget that Advanced MLB Data is now available as part of our 2016 MLB product. What happens if we use some of this advanced data (which few people have the ability to access) and screen for cheap batters who have hit the ball well over the last 12 months?

Step 4: Adv Stats – Year > Distance – Season (Beta) > “200 to 400”

Despite what the low salaries might lead us to expect, we in fact can find a good number of batters who on average have hit the ball pretty far over the last year.

Mitchell Block has written about the value of ISO: What happens if we screen for cheap outfielders facing pitchers whose handedness boosts their ISOs on a relative basis?

Step 5: Stat Split Filters > ISO Diff > “0.01 to 1.5”

Unsurprisingly, the players who in the past have matched this fairly straightforward trend have performed well. Also unsurprisingly, because of the filters we have selected, our sample size — though not small — has shrunk significantly. As you should expect, cheap players who aren’t actually bad are not common.

As I write this around 6:30 AM ET, who are the cheap outfielders in this slate who presently fit the trend we’ve created?

Current Matches

Remember that throughout the day (after this is published) some adjustments to lineup orders will be made and so this list could change (and likely expand), but as of now this is an intriguing list. Carl Crawford, in particular, batting in the sixth spot, could make for a compelling tournament play with his likely low ownership.

Of course, there is one more factor we might want to take into account: the season is very young.

Step 6: Time Filters > Month > “April and May”

Yikes. As you can see in the screenshot, April is the worst month of the season for cheap outfielders, and May is easily the second-worst month. These batters, on average, are still productive players across these months — with how well they hit the ball and how cheap they are, it would be hard for them not to be productive — but perhaps we should temper our expectations for these batters. As Bryan Mears has pointed out, the early part of the MLB season is very unpredictable. It could be very natural for this trend to be less applicable in April and May.

At the same time, the April-May sample of 289 batters is relatively small, and if you look through the past results you will find many batters — some of whom are in the bottom half of the order — who far exceed expectations. Clearly, we can’t ignore the time of the season. Still, it’s not certain that we should let it play a huge role in our decision-making process as regards players matching for this trend.

The Takeaway

So here’s how I think that you could use this trend. If you find a player you like who fits this trend, don’t be afraid to use him, knowing that he is a good hitter who belongs to a productive, inexpensive cohort. At the same time, perhaps adjust your expectations downward slightly, knowing that historically the outfielders who fit this trend have been at their least productive early in the season.

Don’t avoid a player early in the season because of this trend. Just don’t count on him to be the guy who makes a huge difference in your lineup.

Good luck!