Baseball is a sport in which a runner can get “Runs” only when there is a batter who raises an RBI. And since each batter receives equal opportunities to bat, it is impossible to funnel more offensive opportunities into a standout player. Therefore, player composition is particularly important. In this study, we checked whether the batter composition information could be usefully used to predict team runs more accurately. Players were given a grade for each evaluation index based on individual evaluation indicators. Such as batting average(AVG), on-base percentage(OBP), slugging percentage(SLG), OPS(On-Base Plus Slugging), wOBA(weighted On Base Average), wRC+(Weighted Runs Created), and the player distribution information for each grade was used to predict team runs. As a result of the experiment, it was confirmed that the team runs were predicted more accurately if we used the player distribution information by grade with team's batting statistics than used only team's batting statistics. The method proposed in this study considers the number of players in each grade to predict the team's scoring ability. So it is useful not only in improving prediction accuracy but also in predicting the level of the team's scoring ability hierarchically among teams with similar statistic values.