by Chris Harrington

Contents

1. 1 by Chris Harrington
2. 2 Query
3. 3 Initial Thoughts
4. 4 My approach
5. 5 Results
   1. 5.1 Graph
   2. 5.2 Distribution of Wrestlers by Televised/PPV Win Record by Year
   3. 5.3 Analysis
   4. 5.4 Full list of wrestlers by year 
      1. 5.4.1 1980
      2. 5.4.2 1981
      3. 5.4.3 1982
      4. 5.4.4 1983
      5. 5.4.5 1984
      6. 5.4.6 1985
      7. 5.4.7 1986
      8. 5.4.8 1987
      9. 5.4.9 1988
      10. 5.4.10 1989
      11. 5.4.11 1990
      12. 5.4.12 1991
      13. 5.4.13 1992
      14. 5.4.14 1993
      15. 5.4.15 1994
      16. 5.4.16 1995
      17. 5.4.17 1996
      18. 5.4.18 1997
      19. 5.4.19 1998
      20. 5.4.20 1999
      21. 5.4.21 2000
      22. 5.4.22 2001
      23. 5.4.23 2002
      24. 5.4.24 2003
      25. 5.4.25 2004
      26. 5.4.26 2005
      27. 5.4.27 2006
      28. 5.4.28 2007
      29. 5.4.29 2008
      30. 5.4.30 2009
      31. 5.4.31 2010
      32. 5.4.32 2011
      33. 5.4.33 2012
      34. 5.4.34 2013

Query

Matt D. writes:

Chris,

Do you think that there might be a statistical correlation between the birth of smackdown and the start of the "even-stevens" booking in the WWF? If not, then maybe with the death of WCW and the end of the Monday Night wars? If so, is it something that dropped with the brand split and less TV or maybe rose after Lesnar left and WWE might have been less apt to push someone as The Man? 

Any thoughts?

Initial Thoughts

It's a good question. Obviously, there's challenges in quantifying what "even-steven" booking really refers to. Are we talking about person A and person B trading wins between each other? Are we talking about a lack of people being treated as "special" and exempt from losing? Are we discussing the idea that as a whole even the "pushed" wrestlers are losing at random moments to opponents that should be "beneath" them? (That's a lot of "quotes", eh?)

I could approach this by looking at some form of OCELOT ratings where we see what percentage of wrestlers "move up" a significant amount in rankings over a period of time and how that compares across eras. We could do that. However, that's not how I decided to approach it.

My approach

1. Collect and process WWF/WWE results from 1980-2013 from CageMatch
2. Filter to TV/PPV matches (excluding Dark Matches)
3. Calculate win-loss records for each wrestler and total number of TV/PPV matches by year
4. Include all wrestlers that have at least 20% of the maximum number of TV/PPV matches for that year (i.e. Bryan/Cesaro had most TV/PPV matches in 2013 at 102 so cut-off would be 21 matches meanwhile Tony Garea lead the 1981 list at 41 matches so cut-off was 9 matches)
5. Categorize each wrestler's annual win-loss record into one of four categories: High [Above 71%], Mid [between 54% and 71%], Low [35% to 53%], Very Low [below 35%]. (These four buckets were chosen so that across the entire time-period, there would be an even distribution in each bucket.)
6. Calculate what percentage of wrestlers from each year fall into each bucket over time.

Results

Graph

Analysis