Fantasy Toolbox: Teams Runs vs Team Saves

Fantasy Toolbox: Teams Runs vs Team Saves

Fantasy Toolbox: Teams Runs vs Team Saves

This is one of our first—hopefully of many– comment response articles. Below is the comment, from YardBarker Jeff:

Great stuff, Kman. Iâ’d love to know if there is a correlation between saves and runs scored. This is a small sample size, but of the top ten teams in runs scored, 4 of them are top ten in saves. At the same time, the yankees have scored the most runs in the league and have yet to record a save. Thinking out loud here, but if the yankees have scored the most in the league (91) and are 22nd in the league in runs allowed (53), itâ’s possible there is a correlation between saves and the differential between runs scored and allowed. What do you think?

Good questions. I ran both using the following criteria;

  • I stuck with the same 180 teams that were used in the previous Fantasy Toolbox: Closers & Saves
  • Since the last article broke the teams into groups of four I did the same here. Using simple math, 180 divided by 4 groups = 45. So each group contains blocks of 45 teams & seasons. The first group will be the Top 45, the second will be 46 – 91, etc, etc.

Runs Scored vs Saves

RS Ranking Average Wins Average RS Average Saves
Top 45 87.5 882.42 41.04
46 – 90 87.04 794.82 41.84
91 – 135 77.64 742.93 40
136 – 180 71.53 679.38 38.58

The runs scored test didnâ’t give any real indication to RS vs Saves. In-fact, the second grouping outpaced the Top 45. From this, we can conclude that being a high scoring team doesnâ’t give a closer an increased number of saves.

Runs Scored vs Runs Allowed Differential

Team Diff Average Wins Average Diff Average Saves
Top 45 95.02 137.71 44.4
46 – 90 85.6 48.44 42.511
91 – 135 76.93 -36.78 39.4
136 – 180 66.2 -149.38 35.11

Here we go! As average wins illustrates, having a strong RS vs RA translates directly to victories. Fans of the Pythagorean Records know this fact well. It also looks like this differential translates directly into the save category, with each save value falling in line with the run differential. Hereâ’s a chart with a Linear Trendline:

Run Differential vs Team Saves

Fantasy Advice: If you havenâ’t read it yet, go back to the first Fantasy Toolbox on Saves & Closers. I think we can take the lesson learned there, which was teams with higher win totals yield more saves. Couple thatwith the new run differential data that weâ’ve learned today and we have something more concrete. For simplicities sake, we can take todayâ’s findings of differential and assumeits impactupon overall team wins. This is a pretty short leap. Teams with good win totals will usually have a strong run differential at the end of the season. On draft day, keep it simple & tier closers and teams based upon wins. After that, be prepared to dominate your league in the saves category.

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