LineupOpti scores batting orders with metrics built for how baseball is actually played — in sequence, with runners on base. Here is what each one means, how to read a good score from a bad one, and the workflow for building your own optimized lineup.
Traditional stats grade a hitter in a vacuum. Ours grade them in context — who bats ahead of them, who bats behind, and how that combination turns into runs.
How much run value a hitter creates given the runners around them — not in isolation.
For every four-batter sequence we multiply each hitter's stat-based outcomes against the batters ahead of them, weight each result by its RE24 run impact, and sum it. A slugger hitting behind high-OBP batters is worth more than the same slugger leading off with the bases empty — BRP captures exactly that context.
The half of BRP that comes from keeping the inning alive and reaching base.
GOB rewards the outcomes that extend an inning and put a runner on for the hitters behind you — walks, singles, and avoiding outs. It is the 'table-setting' portion of a player's run production.
The half of BRP that comes from advancing runners and driving them home.
PUDI rewards the outcomes that move existing runners forward and score them — extra-base hits and productive contact. It is the 'run-producing' portion. By construction, GOB + PUDI = BRP for every player.
The lineup-level score: every player's BRP aggregated across all nine spots.
Net RPC measures the whole batting order relative to a league-average baseline of zero. Positive RPC means the sequencing creates synergy and scores more efficiently; negative RPC means the order is leaving runs on the table. Reordering the same nine players typically swings RPC by 3–25%.
Lineup-level scores are anchored to a league-average baseline. Net RPC sits at zero for a perfectly average order; Expected Runs / Game is grounded in the ~4.5 runs a typical MLB lineup produces. Use these tiers as a quick read on how an optimized order stacks up.
| Tier | Net RPC | Exp Runs / Game | What it tells you |
|---|---|---|---|
| Elite | ≥ +0.50 | ≥ 5.3 | Top-tier sequencing — runners are rarely stranded. |
| Above Average | +0.15 to +0.50 | 4.8 – 5.3 | Clearly better than a typical order; meaningful synergy. |
| Average | −0.15 to +0.15 | 4.3 – 4.8 | Roughly league baseline — neither helping nor hurting. |
| Below Average | < −0.15 | < 4.3 | Inefficient order; runs are being left on the table. |
General guidance, not hard cutoffs. These bands are directional — exact values shift with the league, season, and the caliber of players you load in. The signal that matters most is the delta: how much the optimized order improves on the one you submitted.
Individual BRP, GOB, and PUDI are best read relative to the rest of the lineup rather than against a fixed scale. In the results table the app shades each row on a red-to-green gradient: green rows are your strongest producers in that spot, red rows your weakest. A high GOB with lower PUDI marks a table-setter; the reverse marks a run-producer.
From sign-up to results. Use the arrows or dots to step through the full flow.
You know what the numbers mean and how to read them. Now put nine players in and let the model find the order that scores the most runs.
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