Batting Stats 10: wRC+

I will be writing this as I work through it, so this may be a little disjointed and have some false starts, but what the heck.

wRC+ is similar to wRC and wRAA in that it measures runs created by a batter in a particular league-year context.  The most significant differences are that wRC+ is a rate statistic rather than a counting stat- scaling to a 100 scale for easy interpretation.  The second biggest difference is that this stat is league and park adjusted.  This allows us to compare players across years and leagues.

The park and league adjustments present some challenges, though.  First, I was warned not to use the park factors from the park tables.  This is a huge bummer because it would have saved me a ton of difficult work.  In fact, I am going to try using the park factors from that table as a starting point, just to be sure it won’t work.  I am really not looking forward to doing those calcs myself.

The league adjustments won’t be as big of an issue. I can use the team_affiliations table to determine subleague (i.e. AL vs NL) for each player – or I can ignore it altogether.  I am thinking of disregarding subleagues because I haven’t noticed much difference between my leagues in game play.  I never use the DH, so offense isn’t skewed by that.  I will try it and see how easy it is.

The formula, per Fangraphs, is:
((wRAA/PA + League Runs Per PA) + (League Runs Per PA - (Park Factor*League Runs Per PA) / (Subleague wRC/PA)) ALL x 100 

Let’s break this down bit by bit.

• Step 1: (Player wRAA / PA +
  • Will have to decide whether to elaborate the wRAA formula or use a variable in its definition, but very easy aside from that.  I will try it as a variable first.
• Step 2: League Runs Per PA) +
  • Knowing that this would end up as part of the wRC+ calculation, I added it to the League Runs Per Out view I created in the Run Environment section.  And since we already referenced that view for wRAA, we can simply reference it here as RperPA
• Step 3: (League Runs Per PA –
  • Same as Step 2
• Step 4: (Park Factor * League Runs Per PA) / 
  • If the park factor from the parks table can be used as a reasonable substitute – and I’m really hoping it can – then this is pretty straightforward.  I would join to parks on team_id and return the park factor (avg).  If can’t be used, then I’m off down a rabbit hole to calculate those park factors.
• Step 5: (Subleague wRC/Subleague PA)
  • Here’s a weird thing: Subleague wRC.  Just like a league wOBA is really just OBP, wouldn’t league wRC just be runs?  Let’s look at the wRC formula again as it would apply to the league:
    • League_wRC = (((League_wOBA-League_wOBA)/wOBA Scale)+(League_R/League_PA))*League_PA
      • League_wOBA – League_wOBA = 0.  And 0 divided by anything is 0.  So, we evaluate to: 0 + (League_R/League_PA))*League_PA
      • League Runs Per Plate Appearance times Plate Appearances = League Runs.
  • So that leaves us with Subleague_Runs divided by Subleague_PA – the same RperPA stat that we’ve used above, just at the subleague level.
• Step 6: x 100
  • Self explanatory, really.

I have to do something about identifying subleagues and summing their data before I start coding this formula.  At this point, I only need runs and PA.  Since I am eager to keep moving, those are the only stats I’ll create.  I created a quick table with those summed stats, joining on the team relations table:

DROP TABLE IF EXISTS sub_league_history_batting;
CREATE TABLE IF NOT EXISTS sub_league_history_batting AS
   (SELECT b.year
      , b.league_id
      , t.sub_league_id
      , sum(b.PA) as slg_PA
      , sum(b.r) as slg_r
    FROM CalcBatting b
      INNER JOIN team_relations t ON b.team_id=t.team_id AND b.league_id=t.league_id
      INNER JOIN players p ON b.player_id=p.player_id
    WHERE p.position<>1
    GROUP BY b.year, b.league_id, t.sub_league_id
   );

OK, before the results, let’s set some initial expectations.  Fangraphs‘ rule of thumb chart is below.  It suggests, I think, that if I get within 10 points, I can trust that I’m in the right ballpark.  It won’t be super accurate for precise comparisons between players, but I can probably trust it for general analysis.

And here are the results – randomly selected player years.

Pretty ugly, actually.  19 of 30 are in the happy zone.  Of course, the happy zone is really much bigger than I would like it to be.  8 are borderline, and the remaining 3 are just awful.  Some are high; some are low.

At this point, I am not comfortable using this stat as a basis for any decision-making.  I’m also not ready to dive in and determine the park factors.  So, at least for the time being, I am going to leave this here and move on to pitching stats.

Here’s the script:

#Calculated batting stats for OOTP
    DROP TABLE IF EXISTS CalcBatting;
    CREATE TABLE IF NOT EXISTS CalcBatting AS

    SELECT b.year
    , b.league_id
    , b.player_id
    , b.stint #We can eventually move this down the list
    , b.split_id #We can eventually remove
    , b.team_id #We can eventually move this down the list
    , l.abbr as Lg
    , t.abbr as Team
    , b.g
    , b.ab
    , @PA := b.ab+b.bb+b.sh+b.sf+b.hp AS PA
    , b.r 
    , b.h
    , b.d
    , b.t
    , b.hr
    , b.rbi
    , b.sb
    , b.cs
    , b.bb
    , b.k
    , b.ibb
    , b.hp
    , b.sh
    , b.sf
    , b.gdp
    , b.ci
    , @BA := round(b.h/b.ab,3) AS ba
    , round(b.k/@PA,3) as krate
    , round((b.bb)/@PA,3) as bbrate
    , @OBP := round((b.h + b.bb + b.hp)/(@PA-b.sh-b.ci),3) AS obp
    , round(100*(@OBP/r.woba),0) as OBPplus
    , @SLG := round((b.h+b.d+2*b.t+3*b.hr)/b.ab,3) as slg
    , round(@OBP+@SLG,3) as ops
    , round(@SLG-@BA,3) as iso
    , round((b.h-b.hr)/(b.ab-b.k-b.hr+b.sf),3) as babip
    , @woba := round((r.wobaBB*(b.bb-b.ibb) + r.wobaHB*b.hp + r.woba1B*(b.h-b.d-b.t-b.hr) +
       r.woba2B*b.d + r.woba3B*b.t + r.wobaHR*b.hr)
       /(b.ab+b.bb-b.ibb+b.sf+b.hp),3) as woba
    , @wRAA := round(((@woba-r.woba)/r.wOBAscale)*@PA,1) as wRAA
    , round((((@woba-r.woba)/r.wOBAscale)+(lro.totr/lro.totpa))*@PA,1) as wRC
    , ROUND((((@wRAA/@PA + lro.RperPA) + (lro.RperPA - p.avg*lro.RperPA))/(slg.slg_r/slg.slg_pa))*100,0) as 'wRC+'
    FROM 
      players_career_batting_stats b 
      INNER JOIN leagues l ON b.league_id=l.league_id 
      INNER JOIN teams t ON b.team_id=t.team_id
      INNER JOIN tblRunValues2 r ON b.year=r.year AND b.league_id=r.league_id
      INNER JOIN vLeagueRunsPerOut lro ON b.year=lro.year AND b.league_id=lro.league_id
      INNER JOIN parks p ON t.park_id=p.park_id
      INNER JOIN sub_league_history_batting slg ON t.sub_league_id=slg.sub_league_id AND b.league_id=slg.league_id
    WHERE b.ab<>0 AND b.split_id=1
    ORDER BY b.player_id, b.year