The dynamic game of Daily Fantasy Sports (DFS) requires much more than simply knowing the sport for which we’re entering contests to be successful. We must be adaptable, precise, and open to learning from previous endeavors, the latter of which will be the primary focus of this weekly written piece. Game Theoretic methodologies will allow us to analyze and dissect the previous week’s winner of the largest and most prestigious Guaranteed Prize Pool (GPP) tournament on DraftKings – the Millionaire Maker. These same tenets of Game Theory, which can most simply be explained as the development of decision-making processes given our own skill and knowledge, assumptions of the field based on the cumulative skill and knowledge of others playing the same game, and the rules and structure of the game itself, will allow us to further train our minds to see beyond the antiquated techniques of roster building being employed by a large portion of the field. Approaching improvement through these methods will give us insight into the anatomy of successful rosters and will help us develop repeatably profitable habit patterns for the coming weeks. We’ll start by looking at the previous week’s winning roster, extract any pertinent lessons for future utilization, and finish with a look ahead towards the coming main slate.
Winning Roster
Lessons Learned
Recency Bias
The term “recency bias” relates to human psychology and is a major tenet of Game Theoretic methodologies. Innate human psychological tendencies filter decision-making processes towards stability and the known, allowing biases to be introduced to the field’s decision tree (a visual representation of the path of decisions that lead to a result; in the case of DFS, the result is a roster). Five of the top six running backs in Week 1 usage were on the main slate for Week 2:
- Saquon Barkley – 82% snap rate, 74% route participation rate, 37% team target market share, and 33% targets per route run.
- Christian McCaffrey – 83% snap rate, 77% route participation rate, 23% team target market share, and 17% targets per route run.
- Jonathan Taylor – 76% snap rate, 61% route participation rate, 13% team target market share, and 18% targets per route run.
- Leonard Fournette – 76% snap rate, 76% route participation rate, 7% team target market share, and 9% targets per route run.
- Darrell Henderson – 82% snap rate, 78% route participation rate, 13% team target market share, and 13% targets per route run.
- Dalvin Cook (not on the main slate) – 77% snap rate, 79% route participation rate, 12% team target market share, and 12% targets per route run.
Notably, all five of the running backs on the main slate with the highest usage from Week 1 failed to crack the winning roster in the Millionaire Maker, with user madcow65 instead utilizing the contrarian pairing of Jeff Wilson Jr. (a staple from our look ahead last week) and Nick Chubb.
Leverage
The top expected game environments heading into the weekend were Arizona/Las Vegas and Washington/Detroit, meaning those were the two games where ownership was likely to congregate. That said, the former ended up seeing elevated ownership while the latter went relatively under-owned. That brings up the idea of leverage, where we look to ownership as a primary contributor to our decision-making matrix. The reason we look to ownership as a primary contributor to our decision-making matrix is due to the payout structure found in GPP tournaments, where most of the profits are found in the top 5-10 positions. This means the dominant theory in our decision-making processes becomes payoff dominance, which means we’re not only concerned about what we are doing but also must be concerned with what others are doing. That brings us full circle back to the idea of leverage. You’ll notice that the winning roster limited exposure to the highest-owned game environments by selecting only one player from each, instead targeting a different game environment as its primary stack (more on this below).
Defense
The Bengals defense was projected for around 30% ownership throughout the week, which makes sense on paper as they were priced at only $2,200 and were set to play a Cowboys team playing without Dak Prescott. That said, we must first consider how defensive points are scored in DFS before continuing the analysis. The major contributors to defensive points in DFS are defensive touchdowns (six points), turnovers (interceptions and fumble recoveries – two points), and sacks (one point). These are all highly variant acts – as in, they are all hard to predict. Now consider the likeliest game plan for a Cowboys team without its starting quarterback – were they likeliest to approach the game by asking Cooper Rush to throw the football at a heightened rate or were they likeliest to ride their dynamic duo at running back behind a top 10 offensive line? Fewer drop backs for their quarterback means less opportunity for the Bengals to create pressure in the backfield, which means less opportunity for sacks and turnovers to be generated. Madcow65 chose to pivot to the Jaguars defense against a Colts team without its top two pass game options in Michael Pittman and Alec Pierce, a decision that netted him or her an additional 17 fantasy points. The learning point here is to shy away from defenses with high expected ownership, considering the ways in which points are scored at the position are highly variant acts. The way I teach this aspect of DFS play is to embrace variance at a position with high intrinsic variance.
Game Environment
Targeting game environments is a way to reduce the number of variables that must “go right” to capture bulk fantasy points. On the winning roster, that idea was present through the primary stack (Tua Tagovailoa, Tyreek Hill, Jaylen Waddle, and Mark Andrews), where a shootout-style game environment led to increased pass game production from each team. Taking a step backward, were there any indicators that the Dolphins/Ravens game could turn into a pass-heavy game environment? Yes! Allow me to explain. The Dolphins finished Week 1 with the highest pass rate over expectation in the league while the Ravens finished seventh in the metric. Pass rate over expectation points to a team’s play calling tendencies in varying situations. The higher the pass rate over expectation, the more aerial aggression a team is said to have. Furthermore, both defenses utilize elevated blitz rates, which leads to increased rates of man coverage in the secondary. Finally, the Ravens were to be without two starting cornerbacks, had injuries to their offensive line, and were without their top two running backs on their depth chart (J.K. Dobbins and Gus Edwards). Add it up and this game environment was ripe for elevated pass rates and subsequent fantasy goodness.
Looking Ahead
Philadelphia/Washington (Game Environment)
The Eagles ended the 2021 season with the fifth-fastest situation-neutral pace of play and maintained that pace into Week 1 of 2022, finishing the week with the third-fastest situation-neutral pace of play (have yet to play in Week 2 as of this writing). Increased pace of play leads to additional offensive plays available, which means more opportunity for fantasy points. The Commanders rank fourth in the NFL in pass rate over expectation and fourth in red zone pass rate over expectation thus far in 2022. Elevated pass rates lead to clock stoppages (incompletions) and bulk yardage. When you pair those two team tendencies, we’re left with a game environment that provides increased paths to fantasy production.
Dalvin Cook (Recency Bias, Pending MNF)
As noted above, Dalvin Cook saw top-six usage at the running back position in Week 1, leading to 25 total running back opportunities (carries plus targets). He was severely overshadowed by the production of Justin Jefferson, leading to a scenario where we might be able to capture elite utilization at lower ownership than he otherwise should carry. The Lions (his opponent for Week 3) ceded 27.9 DraftKings points per game to opposing backfields in 2021 and have allowed 31.1 DraftKings points per game to the position over their first two games to start 2022.
Drake London / Kyle Pitts (Leverage)
Atlanta opened the season with games against the Saints and the Rams, two defenses that are firmly entrenched amongst the top 10 in the league. What’s intriguing is the fact that the Falcons averaged 26.5 points per game against tough opponents (27 against New Orleans and 27 against Los Angeles). The team now heads to Seattle to take on a declining Seahawks defense. London and Pitts have combined to account for 29 targets on 59 Mariota pass attempts through two contests, a clear indication of the concentration of this pass offense. London is priced at only $5,800 and Pitts has slipped all the way to $4,800 on DraftKings for Week 3.
Michael Thomas (Leverage)
Thomas has seen target counts of eight and nine to begin the year and has scored three touchdowns in two games, leading to an average of 20.6 DraftKings points per game. The glaring trend to me is the increase in snap rate in Week 2 (76%) compared to Week 1 (61%), which indicates his return to health following a lost season in 2021. His price for Week 3 is sitting at a palatable $5,900, which provides an interesting leverage opportunity assuming his expected ownership remains low.
Jahan Dotson (Leverage)
We’ll double-dip on Washington as they present opportunity through both game environment and leverage. Dotson’s production has been overshadowed by Curtis Samuel over the first two weeks, but it’s the rookie who leads the Commanders in total snaps played. He’s also already demonstrated his red zone acumen, scoring three times in two weeks, and is priced at only $4,600 on DraftKings for Week 3.
