In an age in which baseball is emphasizing reaching base safely rather than focusing solely on hits, there has been a sharp change in the statistics emphasized in Major League Baseball. Although box scores continue to display the traditional metrics of Batting Average, Runs Batted In (“RBI”), and Hits, professional coaches are beginning to rely more on On Base Percentage (“OBP”), and more advanced metrics including BABIP and Runs Created. Thus, we feel advanced metrics are long overdue at the amateur level. Here at GameChanger, we have tweaked Bill James’ Runs Created stat in order to adjust for the differences between amateur baseball and professional baseball. In this article, we’re going to take a dive into how coaches can incorporate Runs Created into their arsenal of stats to evaluate performance.
Runs Created is a statistic that can be used to measure an individual player’s offensive contribution to the offense. Many believe Runs Created fixes the main flaw of both Runs and RBIs because it only uses the outcomes of a player’s Plate Appearances to calculate their contribution to the team. In contrast, both Runs and RBIs are situational stats that rely on factors out of the batter’s control. For example, in order to score a Run, another player must enable you to score by putting the ball in play, walking, or misplaying the ball. Similarly, in order to get an RBI, there must be other players on base for a hitter to drive in, unless the batter hits a Home Run.
Runs Created attempts to isolate the impact a hitter can make, independent of what other players have done. Thus, by using Runs Created, all players on a team are measured equally. Our tweak to the Runs Created formula and the correlation between Runs Created and Runs Scored for more than 18,000 High School level baseball teams in 2017 can be seen below:1
RC = 1.46 * ( ( H + BB ) * TB ) ( AB + BB )
The major difference between the Runs Created formula used in this analysis and the formula created by baseball sabermetrician Bill James is that we incorporated a coefficient of 1.46 in our formula in order to account for the differential of the ratio of Earned Runs and Unearned Runs between High School level baseball and Major League Baseball. Earned Runs account for 92% of Runs in the Major Leagues, so it was not essential for Bill James to take that into account. However, Earned Runs account for just 63% of Runs at the High School level. Thus, we had to multiply James’ formula by 1.46 (92/63) in order to get an accurate total for High School level teams across the board.
According to the graph, Runs Created is indeed a very good predictor of Runs Scored. The data points do not vary much from the regression line (blue line), indicating that there is a strong correlation between the two stats. The most significant aspect of this graph is the slope of the regression line. The slope of 0.91 is very close to 1, which shows that Runs Created estimates a team’s scoring output very closely over the course of the season.
Moreover, Runs Created is an easy way for coaches to measure the production of their players and see who is really the most valuable offensive asset on the team. Since we showed that Runs Created for a team is an accurate predictor of a team’s run production over the course of a season, it can be valuable in measuring each player’s impact on the offense. Since Runs Created eliminates situational variables, coaches may be surprised by the insights they can extract.For instance, a player who happens to bat more often in poor situations – like many hitters at the bottom of a lineup – would be credited for their offensive output more by using Runs Created than by more traditional metrics.
1 Data from teams composed of players age 13 to 18. Data collected through May 22, 2017.
2 Runs Created per Plate Appearance was used because season lengths vary greatly across the country, and this scale allows us to keep the best teams across the country in the data set.