Let’s dip into the baseball data to see what else we can learn.
Join the DZone community and get the full member experience. We can’t quit you, baseball! The season might be over, but we want more. So, we’re dipping into the baseball data to see what else we can learn. Read on for one more run around the bases! This season, all anyone talked about was home runs. There were 6,770 homers hit during the regular season this year. That’s 665 MORE than the previous record! And exactly half of the teams in the league set franchise home run records. Holy homer! But, do all these home runs lead teams to the playoffs? We looked at the past five years (2014-2019), pulling the top five teams for home runs in each year. Edge colors indicate: Here’s the result: How do other stats affect a team’s success? To find out, we layered in Earned Run Average (ERA), Strikeouts (SO), and Runs Batted In (RBI) one by one. Each of these graphs used separation constraints to pull the statistic nodes (home runs, RBI, ERA, SO) away from each other. This adds a customization layer to the standard symmetric layout. Using the Designer, a spacing specification in the Model Rule forces the layout to pull a team that is connected only to a single statistic closer to that statistic node. For a team connected to two statistic nodes, the pulling happens in both directions, and the team node displays in the middle of the two statistic nodes.
