The Historically Weak Fields in Kitzbuhel and Los Angeles

With the Olympics starting in just a few days, it’s no surprise that this week’s two ATP 250 events barely qualify as sideshows.  No man inside the top 20 is participating in either one, and journeymen such as Bjorn Phau and Blaz Kavcic are seeded.

In fact, Kitzbuhel and Los Angeles sport two of the weakest fields in recent history, handing out some of the cheapest ranking points ever offered by tour-level events.

To the naked eye, it’s plenty clear that these tournaments don’t measure up to the standard of, say, Halle or Doha.  But attaching numbers to those claims is more difficult.  You could compare average or median ranking, the cut, the ranking of the lowest seed, or even the ranking of the top seed.  However, none of these provide the whole picture.

To quantify field strength using just a number or two, in a way that allows us to compare 28-man 250s to 48, 56, or 64-player 500s, to 128-player slams, let’s turn to a method suggested by Carl Bialik.  We’re most concerned with how difficult these tournaments are to win.  So, since some player ranked roughly #10 in the world is in the field at almost every event, let’s compare the probability that the #10-ranked player would take the title.

At most grand slam and masters-level tournaments, the #10 player in the world has a 1-3% chance of winning.  It’s awfully unlikely, though definitely nonzero.  At a lower-level tournament like Atlanta last-week, the #10 player–in this case, John Isner–was the most likely winner, though he had some high-quality competition from Mardy Fish, Kei Nishikori, and eventual winner Andy Roddick.  In more extreme cases, like this week’s Los Angeles event, no one inside the top 40 is participating.  So if #10 entered, he would be the overwhelming favorite.

The field in Kitzbuhel this week is so weak that, had a hypothetical #10 player entered, he would have a 45% chance of winning the title.  That’s the highest we’ve seen on the ATP tour in at least the last four years.  The LA draw is stronger in this regard.  Thanks in part to the currently underrated Sam Querrey, the hypothetical #10 would have a mere 31% chance of winning.  As we’ll see in a moment, though, that doesn’t tell the whole story.

10 events have had sufficiently weak draws to give the #10-ranked player a 30% or better chance of winning, but Kitzbuhel is the worst of all.  Los Angeles, while relatively stronger, is the weakest hard court event.  In the last year, there have been 42 events flying the ATP 250 banner.  By this metric, the average 250 draw would give the #10 player a 23.6% of winning.  By comparison, the #10 player has, on average, a 10.4% chance of winning an ATP 500 event.  (Hamburg last week was an aberration, clocking in at 22%, higher than half of the 250s.)

Much like next week’s 500-level event in Washington, LA’s Farmers Classic is a direct casualty of the Olympics.  As part of the US Open Series, it typically attracts quite a few top hard-courters.  Last year’s field included both Fish and Juan Martin Del Potro, and the #10 player would have a had mere 16% chance of winning, on par with the relatively strong 250 fields in Buenos Aires and ‘s-Hertogenbosch.

A slightly different metric exposes the true dearth of quality players in Los Angeles this week.  In addition to calculating the probability that the #10 player would win, we can check the probability that the #50 player would win an event.  For a draw of any quality, that number is close to zero.  For these weaker 250 fields, the additional perspective gives us more nuance.  If an event is packed with guys ranked around #100, as LA is, it is easy pickings for someone like Benoit Paire or Xavier Malisse.  If there are plenty of top-70 or top-80 players, the #50 entrant will have a much tougher time.

Measured by the probability of the #50 player winning an event, Los Angeles has the weakest field of any tournament back to 2009.  The hypothetical #50 would have an 11.7% chance of winning, better than the chances for the #10 player in Doha, Halle, or Queen’s Club!  It’s also the only time I found that #50 would have been better than a 10% chance.  Unsurprisingly, Kitzbuhel checks in near the top, in third place, with a 6.9% chance of the #50 player winning.

To some extent, the Olympics are to blame.  But more generally, it is a reminder than all ranking points aren’t created equal.  It’s another flaw in the ranking system: Simply because the ATP awards the same 250 to a wide range of events does not mean that they are equally challenging.

Put another way, the massive gaps between 250s (and, to a lesser extent, 500s) are an opportunity for enterprising players.  While some players were resting last week, Juan Monaco picked up the cheapest 500 points on offer all year to jump into the top ten.  In Washington, another cheap 500 will go to a player who probably would’ve lost in the first two rounds at the Olympics.  There may be more to tennis than ranking points, but there’s certainly more to ranking points than meets the eye.

Below, find more on the rather complicated methodology of this study, along with a table comparing all tournaments of the last 52 weeks.

Calculating the probability that the #10 or #50 player would win a given tournament is a process with many steps.  I’ve defined “#10” as the tenth-best player on the tournament’s surface, measured by jrank, at the time of that tournament.

If that player is already in the draw, I run several thousand simulations of the draw to determine each player’s probability of winning.  To avoid the biases inherent in any specific draw, I re-generate the bracket.  Thus, the percentages reflect only the strength of the field, not the quirks of who plays who in the first or second round.

If the player is not already in the draw, an extra step is necessary.  First, I identify the next-highest ranked player in the draw.  (That is, #11, #12, and so on, not #9 or #8.)  I replace that player with the “target” #10 player.  I then reseed the draw, so that if the #10 player would have been seeded, he is seeded for the simulation.  Finally, I run several thousand simulations, once again re-generating the bracket each time.

For #50, repeat the process with the fiftieth-best player on the surface instead of the tenth.

Below, find all of the tournaments from the last 52 weeks, ranked by the probability that the #10 player would have won.  Note that clay events dominate the top of the list.  In part, that’s simply because the top players, with the occasional exception of David Ferrer, don’t bother with any of those.  It’s also because those draws are often full of players who are stronger on hard courts, as is the case in Kitzbuhel this week.

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)  
2012  Kitzbuhel              250     Clay  44.5%   6.9%  
2012  Belgrade               250     Clay  42.3%   5.1%  
2012  Santiago               250     Clay  39.5%   5.7%  
2012  Casablanca             250     Clay  39.1%   4.8%  
2011  Bucharest              250     Clay  39.1%   8.4%  
2012  Bucharest              250     Clay  37.7%   3.6%  
2011  Kitzbuhel              250     Clay  35.7%   4.0%  
2012  Umag                   250     Clay  35.3%   3.1%  
2012  Los Angeles            250     Hard  31.3%  11.7%  
2011  Moscow                 250     Hard  29.9%   3.8%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2012  Bastad                 250     Clay  29.4%   3.0%  
2012  Stuttgart              250     Clay  29.1%   2.4%  
2012  San Jose               250     Hard  27.9%   3.5%  
2012  Costa Do Sauipe        250     Clay  27.3%   2.1%  
2012  Gstaad                 250     Clay  26.5%   1.6%  
2012  Nice                   250     Clay  25.9%   1.4%  
2012  Chennai                250     Hard  25.4%   3.7%  
2012  Munich                 250     Clay  24.5%   1.9%  
2012  Auckland               250     Hard  24.3%   2.7%  
2012  Estoril                250     Clay  23.8%   2.3%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2012  Zagreb                 250     Hard  22.6%   4.5%  
2012  Hamburg                500     Clay  22.1%   1.8%  
2012  Sydney                 250     Hard  20.4%   1.6%  
2012  Atlanta                250     Hard  20.2%   2.9%  
2011  St. Petersburg         250     Hard  20.1%   2.5%  
2011  Stockholm              250     Hard  19.5%   1.6%  
2012  Montpellier            250     Hard  19.4%   2.0%  
2011  Kuala Lumpur           250     Hard  18.7%   2.2%  
2012  Houston                250     Clay  18.3%   1.5%  
2011  Vienna                 250     Hard  18.2%   1.5%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2011  Winston-Salem          250     Hard  17.6%   2.9%  
2012  Memphis                500     Hard  17.6%   2.1%  
2012  Newport                250    Grass  17.5%   4.4%  
2012  Marseille              250     Hard  17.0%   1.0%  
2012  Delray Beach           250     Hard  16.8%   2.3%  
2012  s-Hertogenbosch        250    Grass  16.7%   3.8%  
2012  Buenos Aires           250     Clay  15.5%   1.0%  
2011  Metz                   250     Hard  14.5%   1.8%  
2011  Bangkok                250     Hard  13.7%   1.5%  
2011  Washington             500     Hard  13.2%   0.7%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2012  Eastbourne             250    Grass  12.8%   2.7%  
2012  Acapulco               500     Clay  12.5%   0.9%  
2012  Brisbane               250     Hard  12.0%   1.5%  
2012  Rotterdam              500     Hard   9.9%   0.8%  
2011  Beijing                500     Hard   9.8%   0.9%  
2011  Valencia               500     Hard   9.8%   0.9%  
2012  Queen's Club           250    Grass   8.3%   0.8%  
2012  Halle                  250    Grass   7.0%   0.5%  
2012  Doha                   250     Hard   6.7%   0.7%  
2011  Basel                  500     Hard   5.9%   0.4%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2011  Tokyo                  500     Hard   5.7%   0.6%  
2011  Shanghai Masters      1000     Hard   5.5%   0.1%  
2012  Dubai                  500     Hard   4.2%   0.3%  
2012  Barcelona              500     Clay   3.9%   0.2%  
2011  Paris Masters         1000     Hard   3.1%   0.1%  
2011  Cincinnati Masters    1000     Hard   2.6%   0.1%  
2012  Monte Carlo Masters   1000     Clay   2.6%   0.0%  
2011  Canada Masters        1000     Hard   2.5%   0.1%  
2012  Indian Wells Masters  1000     Hard   2.5%   0.0%  
2011  US Open               2000     Hard   2.1%   0.1%  

YEAR  EVENT                  PTS  SURFACE  p(10)  p(50)
2012  Australian Open       2000     Hard   2.1%   0.1%  
2012  Miami Masters         1000     Hard   2.1%   0.0%  
2012  Roland Garros         2000     Clay   2.0%   0.0%  
2012  Rome Masters          1000     Clay   1.9%   0.0%  
2012  Wimbledon             2000    Grass   1.6%   0.1%  
2012  Madrid Masters        1000     Clay   0.8%   0.0%

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