Simply "knowing more" once provided a huge advantage in fantasy baseball. Newspapers and web sites did the legwork for you. Today social media provides knowledge in real time, and sabermetric analysis is widely available. When access to information is equal, one can gain an edge by exploiting weak spots in conventional wisdom. One such example is a huge bug in valuation theory.
With the "current events" playing field leveled, understanding the application of sabermetric analysis to fantasy baseball evaluation became the next means of staying ahead of the curve -- and it remains so. As the depth of sabermetric analysis has grown, so has its accessibility. Again though, the Internet serves as the conduit, so anyone can gain this edge if they're willing to put in the work.
Which brings us to conventional wisdom about player valuation. Regardless of the system, one of the tenets of valuation is the draft-worthy pool is composed of the exact number of players necessary to fill everyone's active roster. For example, in a 12-team league with 14 active hitters and 9 active pitchers, 168 hitters and 108 pitchers have positive projected value. The intrinsic assumption is these 276 players are the only ones to be active in the league all season. Of course, this is simply not the case.
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Valuation models need to adhere to this convention since all we care about on draft day is filling our active rosters. We're paying what is necessary to roster each player relative to the expectations of other players. In essence, when winning a player in an auction for $25, you aren't necessarily expecting that player to return $25; you're expecting that roster spot to do so. The same is true in a draft. Each draft spot comes with an expectation level of production, but the player you draft may not account for all of it.
A sage drafter can take advantage of this bug by drafting players not expected to be active every week. The notion is you'll have someone else active on that roster spot when the player is out, accumulating stats which can be added onto those of the originally drafted players.
The easiest way to demonstrate this ploy is deciding how much to pay for, or where to rank Francisco Tatis Jr. (pictured). He's the best example since it's known how long he'll be out. Granted, how he'll play is clearly unknown since he's not only returning from a long layoff after his suspension, but he's only coming back from shoulder surgery and a wrist issue. For the sake of this discussion, let's assume Tatis Jr. returns at, or close to his previous level. Once the method is explained, everyone's own estimation of his production can be rolled into the process.
Tatis Jr. needs to sit out the final 19 games of his suspension, so is eligible to return on Thursday, April 20. In leagues with weekly moves beginning on Monday, you'll get the first series, then two weeks of another player. You can choose to play him the Week of April 17 and take zeroes for a few games, or wait until Monday, April 24 to insert Tatis Jr. into your lineup. Some leagues start the week on Friday, changing the math a little, but hopefully the idea is clear.
Whatever the number of games turns out to be, you can get someone else's stats from that roster spot. Since that player is ostensibly free (a reserve, or acquired as a free agent or waiver pick-up), you can pay a little more for Tatis Jr., using him as the proxy for the extra stats. Quantifying the exact amount is beyond the scope of this discussion, but back of the envelope math renders a week's worth of hitting stats from an average player to be worth around $0.50. Since the substitute player will be on your roster for two to three weeks, adding $1.00 to your bid price covers the extra production. One buck may not seem like much, but it's probably over what many are willing to pay, especially since they now need to go $2 over their desired price (with the caveat everyone has their own expectations and price in mind). The idea is going an extra buck or two, or jumping Tatis Jr. up a spot or two on your cheat sheet isn't "overpaying", since you're also getting some bonus production from that roster spot.
Tatis Jr. is the obvious example to describe the method since the amount of time he'll miss is known, at least at the beginning of the season. This tactic can also be applied to injury-prone hitters and pitchers, but quantifying the "overbid" or draft rank is even more vague since the time element is just a guess. Still, adding a couple bucks onto the bid price for Mike Trout or Aaron Judge could win the player, while still getting a positive return on investment from the draft spot, even though you "overpaid" for the player.
The final means of leveraging this valuation bug is best suited in leagues facilitating moves between the active and reserve, commonly known as streaming, or playing the matchups. Most everyone streams pitching at some level, but if the rules allow it, and the reserve is deep enough, streaming batters is a great way to get an edge.
The idea is all of the innings or plate appearances are plugged into the valuation algorithm to reveal projected earnings. Take Ryan McMahon (or any Colorado Rockies hitter) as an example. His home stats are routinely better than those on the road, but the road stats are included in his valuation input, dragging down the price. What if you deployed McMahon for all home games, and whatever road affairs came long for the ride? On a "per active week" basis, he's going to produce more than his cost. When he's away from Coors, you activate someone likely to add stats better than what McMahon would have contributed. The aggregate player returns more than McMahon's auction price or draft spot. Here again, adding a buck or two to the expected earnings generated from conventional valuation should land you the player, with some buffer to turn a profit.
McMahon's venue is an obvious pathway to finding splits from which to take advantage. Finding players from other hitter-friendly parks works, as does rostering some left-handed batters since there will be transaction periods where they are facing an inordinate number of right-handed pitchers, potentially spiking their number over that span. Using hitters on teams in a division with weak pitching is also viable, though with the new schedule, there will be fewer opportunities to face the lesser hurlers. Picking up free agents with weaker opponents in a given period is probably better than drafting them since they will be sued less frequently compared to the other reserves.
This approach can also be used to add stolen bases since there are teams stronger or weaker at defending the running game. Players whose primary asset is stolen bases are far less likely to run on teams with a good defensive battery while they tend to run wild against squads whose pitcher and catcher don't focus on nabbing would-be pilferers.
The same principles can be used for pitchers. Road stats from arms working half their games in pitching venues probably inflate ratios, lowering their expected production on a per-game basis. The same means of overpaying for pitcher from a team with a offense-suppressing venue helps build an aggregate pitcher whose ratios are better than the season-long numbers of someone you will only use at home.
Taking advantage of this valuation bug is a great way to derive profit from a handful or roster spots. You don't need to determine the exact amount of expected added production since going just a buck or two over the market price or jumping him up a few spot in draft rankings will net you the player.