Daily Fantasy Strategy – First Half Reflections
The mid-way point of the MLB season is a good time for fantasy players to sit back and take stock of their lot in life. For seasonal players, that means identifying areas of improvement and deciding whether to buy or sell in dynasty leagues.
For those who play in daily leagues, though, there’s a lot less to do. If you’re a DraftStreet or Fangraphs The Game addict, the last four days have probably been excruciating. But just because there aren’t set rosters and waiver wires to scourge during the four-day off-period doesn’t mean daily players can’t do some reflecting and improve for the second half.
Take a look at your bankroll compared to the start of the season and evaluate how you’ve done. If you’re meticulous and keep notes on your selections, see if you’ve been playing better in double-up formats or win-it-all formats. Have days with thin schedules hurt your payouts? It’s never too late to alter a gaming and/or investment strategy.
Personally, I’ve used the time off to reflect on some lessons I’ve learned and also try and identify potentially undervalued players for the tail end of the year.
One such lesson: I hate talking about the weather, but it has a real impact on performance. You want to seek warm temperatures and outward blowing winds for hitters for the most part, and even if 15 weather forecasts all blend together at times, they have utility.
Another, although one that we should all know already: daily fantasy can be a lot more frustrating than seasonal fantasy. With a season-long endeavor, bad games or bad beats can even out. The same might be true for daily players, but because your rosters and prices change daily, there’s an element of BABIP for fantasy players as well.
If you’re first half wasn’t as strong as you’d like or if you’ve built a big stack to play with in the second half, the table below shows some potential undervalued players for the second half. Because there are so many bad players expected to improve, I am only displaying players expected to be at least 85 percent of league average down the stretch (players you’re far more likely to invest in).
My methodology was fairly simple – for all players with at least 100 plate appearances, I calculated their total DraftStreet points to date and created a “Pts/PA+,” a quick gauge to show how a player does relative to his peers in terms of gaining fantasy points by the plate appearance. I then did the same using ZIPS rest-of-season projections and compared the two – a player expected to have a higher Pts/PA+ moving forward may be underpriced based on previous performance and vice versa.
Potentially Undervalued 2nd Half Players | ||||
---|---|---|---|---|
Name | To Date Pts/PA+ | ROS Pts/PA+ | Diff | PA ROS |
Luis Cruz | 0.45 | 0.89 | 1.99 | 189 |
B.J. Upton | 0.56 | 1.02 | 1.82 | 255 |
Danny Espinosa | 0.48 | 0.87 | 1.80 | 225 |
Ike Davis | 0.54 | 0.94 | 1.72 | 204 |
Carlos Ruiz | 0.66 | 1.08 | 1.63 | 149 |
Tyler Moore | 0.55 | 0.90 | 1.63 | 162 |
Kevin Youkilis | 0.68 | 1.08 | 1.58 | 162 |
Alex Gonzalez | 0.58 | 0.90 | 1.56 | 129 |
Brett Lawrie | 0.74 | 1.13 | 1.53 | 204 |
Matt Kemp | 0.89 | 1.35 | 1.52 | 223 |
That’s basically a who’s who of first half laggards and shows that, at least in the eyes of ZIPS, one bad half does not mean expectations should be lowered a great deal.
The table below shows basically the flip side, all players expected to perform worse in the second half, using an expectation of league average as the cut off (because you’ll still be investing in above-average players, even if they regress toward a lower true performance level).
Potentially Overvalued 2nd Half Players | ||||
---|---|---|---|---|
Name | To Date Pts/PA+ | ROS Pts/PA+ | Diff | PA ROS |
Matt Tuiasosopo | 1.61 | 0.88 | 0.55 | 159 |
Cody Ransom | 1.26 | 0.81 | 0.64 | 136 |
Jordan Schafer | 1.30 | 0.91 | 0.70 | 150 |
Ryan Raburn | 1.33 | 0.93 | 0.71 | 141 |
Yan Gomes | 1.22 | 0.87 | 0.71 | 143 |
Jose Lobaton | 1.08 | 0.81 | 0.75 | 116 |
Ramiro Pena | 1.10 | 0.83 | 0.76 | 121 |
Jose Iglesias | 1.13 | 0.86 | 0.76 | 182 |
Nick Franklin | 1.09 | 0.84 | 0.77 | 193 |
Ryan Sweeney | 1.24 | 0.96 | 0.77 | 123 |
Kevin Frandsen | 1.24 | 0.99 | 0.80 | 172 |
Again, the list probably isn’t all too surprising, except for perhaps Nick Franklin, who some remain high on. These are mostly part-time players who have done well in spot duty but aren’t expected to maintain that level of performance moving forward.
Blake Murphy is a freelance sportswriter based out of Toronto. Formerly of the Score, he's the managing editor at Raptors Republic and frequently pops up at Sportsnet, Vice, and around here. Follow him on Twitter @BlakeMurphyODC.
Thanks Blake for this solid daily fantasy column – I’ve read the overwhelming majority of them this season and appreciate the effort you put into these. However, since you’re reflecting:
1) How have your picks done so far? I often agreed with your advice on the starting pitching side, but I feel like I ended up with a lot of bad outings along the way this season. What do your picks’ stats look like so far? Have they actually been a good investment for your readers’ fantasy dollar? Brandon Warne does a nice transparent job in his SP steaming series by posting his stats every week, and in general I feel this is a good practice to continue for pick-based Rotographs series.
2) You say in this article that weather makes a difference, but I haven’t seen any data/evidence to back this up – are you sure this is the case? It makes logical sense, but have you objectively determined that weather impacts fantasy stats? If so, which of temperature / wind speed / wind direction / etc. is most important? Conclusions from such a study would surely be interesting to the fantasy community.
Thanks again for a thoughtful daily series.
Hey Matt, thanks for the comment.
1 – I haven’t tracked my DraftStreet picks, probably should. Before we started doing DraftStreet I had tracked my results for the “weekend streamers” post each Thursday (a tough one since I tackle ownership of 50/25/15/5 and rec’d 4 per weekend) and finished up with 4.29 ERA and 4.15 FIP, with 12 wins (41%) and an average of 4.2 strikeouts in nearly six innings. I’m pleased with those results given the limitations. I’ll start tracking Daily recs, tho, to see how they hold up.
2 – Yeah, we’re pretty confident. Some examples:
Wind at Rangers Ballpark – http://www.fangraphs.com/fantasy/daily-fantasy-strategy-76-for-draftstreet/
ZImmerman on temp and wind effects – http://www.fangraphs.com/fantasy/relevant-fantasy-weather-data/
Doubt I have the math/time to do a full-scale study compartmentalizing wind and temp separately, but perhaps that’s an offseason project myself or someone else can do.
BTW if there are any specific parks and/or conditions you’re curious about, let me know, they’ll make for good isolated case studies in this space.
the wind at wrigley is a pretty well known case that could use some numbers backing it up