In part 2 of the lineup starter combo series we showed a win% for each pair. Since a starter rarely pitches a complete game it may not be appropriate to use raw wins even though raw wins are a 100% accurate measure of performance. The next level down in a runs based model is, of course, runs.
For each of the 86,000 games in the dataset we know how many runs a pitcher gave up which is exactly how many runs a lineup gets credit for. The following table shows average runs scored for each lineup-starter tier pair. Tiers are introduced in part 1.
|Lineup-Starter||# Games||Avg Runs|
The tan highlights show two disparate pairs, best lineups and worst lineup paired with each starter tier. The difference between the best lineup vs. best starter and best lineup vs. worst starter is 4.3 to 5.7. It is expected that runs should increase as the starter value decreases. The same difference can be seen win the 5-1 to 5-5 rows above.
Highlighted in green is average lineup vs. average starter which makes up a significant plurality of the games in this dataset. If 4.6 is considered the average (it is close) then runs above or below average can be calculated.
What does this mean? We don’t know. It shows our allocation into tiers may be correct. The above table only shows starters. In the next part we’ll cover lineup-relief for which we also place into tiers. Until then….