The New York Yankees were far and away the busiest team at the August 1st trade deadline, and their decision to “sell” surprised many. As detailed here by MLBTradeRumors, the Yankees traded away 4 active players and a prospect, and received back 10 prospects, 2 major leaguers, and 2 players-to-be-named-later (PTBNL). While the Bronx Bombers are only 5.5 games back of the second wild card spot as of August 3, their decision to sell off aging players and retool for the future is a tried and true strategy that they hope will pay off.
Now that the unofficial second half of the MLB season is underway, every team looks to reassess its approach as the non-waiver trade deadline nears. Underperforming teams look to become “sellers”, while teams confident in their playoff chances seek new infusion of talent as “buyers”. Part of a team’s prospective outlook is its remaining strength of schedule. Teams that over or under performed their talent due to the MLB schedule in the first half may look to benefit in the second half.
Having poor luck with the scheduling can cause an MLB team to underperform, but in addition to this there the luck involved with rotation scheduling. For instance, on two separate occasions, the Braves had to face a stretch of 4 #1 caliber pitchers in a row, and one of these occurred in a stretch of games where 10 of the 12 opposing starters were #1 caliber. Similar “luck” has also occurred for the Phillies and Diamondbacks so far this year. While in some instances the team handled it well, in others it caused extended overall down turns.
This luck applies to both the rotation scheduling of the other team, but also your own, and the disparity between the two. Let’s evaluate the relative strength of rotations that each team has faced over the first half of the season, and the disparity in the quality of their starter versus that of the opposing team. Continue reading Reviewing First Half Rotation Matchup Luck
Earlier this week, Casey Boguslaw posted an excellent article over at Baseball Essential regarding Lineup Optimization. The premise of his argument revolved around comparing a team’s wRC+ and their run production per game. In theory, a team with a low wRC+ but high R/G implies that the lineup has been optimized, i.e. they are squeezing every run out of which they are capable out of the lineup. Conversely, a team with a high wRC+ but low run production is suboptimal, and not scoring as much as they should.
Let’s apply this concept to bullpen use. Each team has a certain number of relievers they are able to use in different situations. Similar to the lineup, different points in the game are more or less crucial. This is tracked by the leverage index (pLi). In a few words, a game situation of average leverage has a pLi of 1, with more intense game situations greater than 1, while less intense situations are less than 1. For a bullpen to be optimized, as the leverage increases incrementally, better and better relievers must be used, i.e. the relationship is roughly linear.