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The Importance of Speed Ratings in Handicapping NXN Nationals

by Bill Meylan ... (November 21, 2008)

 

 

Nike Cross Country Nationals (NXN) is approaching for 2008 (formerly known as NTN). Since the introduction of NTN in 2004, I have predicted team scores for NTN based strictly on speed ratings of the individual runners on each team. Speed ratings compare how fast runners have run relative to other runners ... High School XC speed ratings are derived by a statistical-modeling adaptation of thoroughbred horse speed ratings (also known as Beyer speed figures).

The photo shown is the original cover of the 1975 book that initially described the current method of deriving equine "speed ratings" ... The author (Andrew Beyer) appears on the cover ... Andrew Beyer is a syndicated sports columnist working for the Washington Post ... He is occasionally interviewed during ESPN horse racing telecasts ... The Beyer speed figures (which are available in the Daily Racing Form) are commonly mentioned as part of the handicapping process during telecasts of the Kentucky Derby, Breeders Cup and other important horse races.

Nike Cross Country Nationals (NXN) is contested at a horse racing facility ... Portland Meadows has pari-mutuel wagering on horse races ... Wouldn’t it be interesting if pari-mutuel wagering was available on NXN?? ... If betting was available, Would I bet the race based solely on speed ratings?? - The answer is NO.

Experienced horse-players realize that speed figures are only one factor of the overall handicapping process ... This article discusses speed ratings and other handicapping factors that may be important in predicting the results of NXN.

 

Speed Ratings

Speed ratings are a measure of how fast somebody has run in the past ... an individual speed rating is simply an adjusted race time that somebody ran in a particular race ... It does not forecast the future, it measures the past (just like an individual time from a track meet) ... Speed ratings may be used as factors to predict the future, but that requires human interpretation known as handicapping.

Nike Cross Country Nationals is like the Kentucky Derby (the best runners of a certain age from around the nation meet to determine a champion) ... Unfortunately for us "Speed Figure maniacs", experience has shown that speed figures do not work as well at many national-caliber horse races as they do in more local situations ... they still work OK, but other handicapping factors must be considered before wagering the rent money.

When predicting XC races with speed ratings alone, I view speed ratings in this context ... Speed Ratings are analogous to Seed Times in Track & Field ... Seed times in post-season track meets generally work OK; they are not perfect, but seed times work decently for the intended purpose ... It’s a legitimate method of developing a "Morning Line" for track meets ... I believe the same can be said for speed ratings in XC.

Speed Ratings & Track Seed Times

At the bottom of this page are three tables that illustrates the effectiveness of speed ratings and track seed times to predict the finish positions at several meets:

(1) NTN Nationals 2004-2007
(2) NY Federation and NY State Class Meets in XC for 2008
(3) Nike Outdoor National (NON) Track Championships 2008

Comparing the first two tables (NTN and NY Feds/States), it is obvious that the speed ratings do a better job predicting the NY races than the NTN races ... It is also evident that the seed times used at the NON track meet are similar in effectiveness compared to the NTN speed ratings.

The question becomes - "Why is it more difficult to predict the results of NTN (NXN) and Nike Outdoor Nationals (and races such as the Kentucky Derby)??"

(1) For starters, these races are top quality from top to bottom, and that makes a big difference for handicapping purposes ... State meets around the country typically have some elite teams, mid-level teams and lower-level teams that can be separated by a variety of handicapping methods (speed ratings do a good job in this separation process, and that makes the predicted results quite accurate by comparison).

(2) The accuracy of speed ratings themselves is not as good for some teams nationally as others because I do not follow many NXN-qualifying teams during the course of the season (I briefly rate their State Meets, NXN Regional Meet, and maybe a few other pertinent meets to get a basic overview of their relative team speed).

(3) The high overall quality of NXN means that many teams are very close in ability ... Trying to separate some of these closely-matched teams is difficult (and statistically NOT possible with any certainty) ... Yes - teams like the Fayetteville-Manlius and Saugus Girls do separate themselves, but they are the exception ... When looking at the NON track meet seeds - mere seconds or fractions of a second separate many distance runners (that's a "too close to call" scenario).

(4) Even if speed ratings were 100% perfect (which they are NOT), other handicapping factors (very relevant to NXN) affect team performance which in turn affects team speed for many teams ... When this happens, predictions from speed ratings alone are adversely affected.

 

Nature of the Course

High school XC courses exist is many flavors  - flat, hilly, grass, dirt, rolling, easy, soft, hard, challenging, open, wooded trails, sandy, dusty, wet and Portland Meadows in December ... Portland Meadows in December is different than State Championship Meet courses or NXN Regional qualifying courses ... depending on your point-of-view, this can be either good or bad ... For the New York teams it's been very good.

The old horse racing notion of "Horses for Courses" has been demonstrated over-and-over ... It means some horses can simply race better at certain tracks than others ... Years of horse racing results have proven the following:

(1) Many horses race better on dirt than grass (or vice versa) ... Many champion horses on the grass are only above average horses on the dirt (or vice versa) ... Some horses can perform normally on the new synthetic poly-turf surfaces and some can not.

(2) Some horses are capable of running in the mud and some are not ... A few horses perform exceptionally well in the mud ... A few champion horses become "duds-in-the-mud".

Bottom-Line --> the nature of the course makes a difference in how well many horses perform ... and the same can be said for humans.

In general, champion teams and runners will perform well regardless of the XC course or conditions ... BUT that's "in general" and does not apply to everybody.......
Here is my track & field analogy - The runners attending the National Track Meet have been competing and getting seed times on synthetic tracks ... HOWEVER, assume the National Meet is being contested on an old cider track with a dirt base where it's been raining for a week and the track is flooded and soft ... I agree many top runners will still be top runners, but I also know many runners are going to be affected ....... One scoring XC  runner having a bad race changes the team score (and we all know "Every Runner Counts").

Runners are commonly asked "How fast have you run??" .... When handicapping NXN, I want to answer the question "How fast can they run at Portland Meadows in December??"

How Do You Handicap the Course?? ... There is no way to quantify it in predictions ... And predicting which teams will run well in the Portland Meadow conditions is a guessing game (especially for first-timers over the course) .... However, some teams have shown an ability to run well at Portland Meadows in December (some repeatedly) - These teams get extra consideration (and may get moved up in the speed rating predictions).

Courses & Speed Ratings

Some teams and runners post higher speed ratings at specific courses.  Often, these are courses where they train or race frequently (but not always) ... Sometimes higher ratings come at "speed courses", sometimes at "strength courses" ... When seasonal ratings are available, identifying this type of variation helps refine "which speed ratings should be used in making the morning-line" ... I'm not a big believer in using a team's best speed ratings, especially if it was an exceptional team performance (exceptional performances are not the norm).

NTN Observation --> Most teams will not equal or exceed their speed ratings at NXN (compared to their ratings used to predict NXN) ... their speed ratings at NXN will be generally lower ... WHY?? - One reason is the "nature of the course" and the course conditions ... the sticky mud and cold conditions at Portland Meadows tends to "stretch the runners out" in terms of spacing between runners for such a flat course (and that lowers the ratings for the runners that get "stretched-out").

 

Form Cycle

Horses and humans have other similarities with respect to racing ... Most experience a "form cycle" of some type that includes (1) an improvement-phase [such as getting into shape], (2) a peak-phase [at or near top performance potential; length of the phase varies between individuals], and (3) a decline-phase where the runner can no longer attain top performance levels [may be due to either physical or mental factors].

Being able to predict when runners may improve or have "off-performances" is a very important handicapping factor ... Sometimes it is obvious, but it usually requires some type of human judgment ... With respect to speed ratings, it means manually raising or lowering individually "morning-line" ratings.

With respect to posted team score predictions (especially for NTN), I try NOT to make significant changes in the actual "morning-line" speed ratings (which basically come from recent performances) ... Occasionally a "guess" is necessary when you know about an injury or sickness.

 

Travel & Shipping

Many race horses are not stabled at the tracks where they race; they are shipped in on horse trailers, some over long distances.  Some horses ship nicely over long distances; they get off the trailer, warm-up and then race effectively ... Other horses do not ship well and race poorly.

During the XC season, I try to note various teams that go on over-night trips to new courses (for them) and then compare their speed ratings to their other ratings ... It is not uncommon for some runners to have generally lower ratings on long trips or over-night trips ... It's impossible to predict who will be affected, but it happens enough to be a consideration.

In addition to long distance travel, NXN adds in a series of dinners, festivities and events for the runners ... Somehow, I think this combination will adversely affect the performance of some runners.

 

Trainers & Coaches

Horse handicappers commonly keep statistics on trainers and their success (or lack of success) in specific races (or types of races) at various race tracks ... Some trainers are remarkably successful in certain situations (and handicappers want to know that when betting the rent money).

Likewise in high school XC, certain teams and coaches have proven themselves successful ... Proven success is an important handicapping consideration.

 

Conclusion

Speed ratings have been an effective tool in predicting NTN National results in past years.  However, the nature of NXN and the top-to-bottom quality of NXN teams make it virtually impossible to predict team finishes and team scores as accurately as State Meets or sectional meets within States. Application of other handicapping factors may improve prediction.  However, the unique nature of NXN and the Portland Meadows course in December presents handicappers with an "uncertain" betting scenario .... If pari-mutuel wagering was allowed, I would love it.


 

 

 

       NTN National Races as Predicted (Seeded) by Speed Ratings

              Pred =  Predicted team finish position

              Numbers under the years are the actual finish position for
                the Predicted team ... examples - For the Girls in 2004,
                the team predicted to finish 4th actually finished 11th;
                For the Boys in 2005, the team predicted to finish 1st
                actually finished 2nd.


          -----------------------------------------------------------------------
                  GIRLS NTN                                BOYS NTN
          -----------------------------              ----------------------------
  Pred    2004    2005   2006     2007        Pred   2004    2005    2006    2007
  -----   ----    ----   -------  -----       ----   ----    ----    ------  ----
    1      1       2      10 (a)   1            1      2       2      10 (c)   1
    2      2       1      18 (b)   2            2      1       6      3        6
    3      3       6      1        5            3      17      3      2        13
    4      11      3      2        3            4      8       10     5        19
    5      6       10     6        14           5      13      4      1        7
    6      14      5      7        17           6      6       1      9        9
    7      12      8      17       13           7      5       8      16       5
    8      4       19     8        12           8      7       13     6        12
    9      16      13     5        7            9      10      9      7        2
    10     13      17     16       15           10     11      11     8        4
    11     18      4      19       19           11     15      14     4        10
    12     15      9      4        4            12     9       19     17       3
    13     9       11     15       20           13     14      20     13       17
    14     8       7      13       10           14     20      16     14       8
    15     10      12     14       8            15     12      5      11       11
    16     7       18     12       11           16     21      12     15       14
    17     20      16     9        6            17     3       18     18       15
    18     5       20     11       21           18     17      17     12       22
    19     19      15     20       9            19     19      7      20       18
    20     17      14     3        18           20     16      15     19       20
    21     --      --     --       22           21     18      --     --       16
    22     --      --     --       16           22     --      --     --       21

(a) Midlothian; one top runner broke arm during race (team would likely have finished 5th)
(b) Saugus; team illness (virus)
(c) may have been affected by the "pile-up"		
NTN - On the Girls-side, the biggest discrepancy occurred in 2006 when Southlake Carrol TX was predicted to finish 20th and they actually finished 3rd ... On the Boys-side, the biggest discrepancy occurred in 2004 when Mead WA was predicted to finish 17th and they actually finished 3rd.
 
 

 NY Federation Meet & NY State Class Meet - Prediction vs. Actual Place (using Speed Ratings)

              NY Federation Meet (contested on Nov 15, 2008)
              NY State Class Meet (contested on Nov 8, 2008)

              Pred =  Predicted team finish position

              Numbers under the headings are the actual finish position for
                the Predicted teams ... examples - For the Boys Feds, the team
                predicted to finish 3rd actually finished 4th ... For the Girls
                Feds, the team predicted to finish 10th actually finished 8th


                         Girls  Girls  Girls  Girls  Girls  Boys   Boys   Boys   Boys   Boys
         Boys    Girls   Class  Class  Class  Class  Class  Class  Class  Class  Class  Class
 Pred    Feds    Feds     AA      A      B      C      D     AA      A      B      C      D
 ----    ----    ----    -----  -----  -----  -----  -----  -----  -----  -----  -----  -----
  1       1       2        1      1      2      1      1      1      1      2      1      1
  2       2       1        2      2      1      2      3      2      3      1      2      3
  3       4       3        5      3      3      4      4      5      2      3      4      6
  4       3       4        4      4      4      3      2      3      4      4      5      4
  5       5       5        3      5      6      5      5      4      5      6      3      2
  6       13      7        7      6      5      7      6      7      6      5      6      5
  7       7       16       6      9      8      6      7      6      7      7      8      7
  8       6       6        8      7      7      8      8      8      8      8      7      9
  9       10      10       9      8      9      9      9      9      9      9      9      8
  10      11      8        --     --     10     10     10     --     --     10     10     10
  11      9       11       --     --     11     11     --     --     --     11     11     --
  12      12      14       --     --     --     --     --     --     --     --     --     --
  13      21      9        --     --     --     --     --     --     --     --     --     --
  14      17      13       --     --     --     --     --     --     --     --     --     --
  15      15      12       --     --     --     --     --     --     --     --     --     --
  16      8       15       --     --     --     --     --     --     --     --     --     --
  17      16      18       --     --     --     --     --     --     --     --     --     --
  18      14      17       --     --     --     --     --     --     --     --     --     --
  19      18      19       --     --     --     --     --     --     --     --     --     --
  20      20      20       --     --     --     --     --     --     --     --     --     --
  21      19      25       --     --     --     --     --     --     --     --     --     --
  22      24      21       --     --     --     --     --     --     --     --     --     --
  23      23      26       --     --     --     --     --     --     --     --     --     --
  24      25      22       --     --     --     --     --     --     --     --     --     --
  25      26      24       --     --     --     --     --     --     --     --     --     --
  26      23      27       --     --     --     --     --     --     --     --     --     --
  27      27      23       --     --     --     --     --     --     --     --     --     --
		
 
 

       Nike Outdoor National Track Meet 2008 - Finish Position by Seeds

              Seed =  Seed Time position

              Numbers under the years are the actual finish position for
                the Seed (team or runner) ... examples - For the Girls DMR,
                the team seeded 3rd actually finished 9th ... For the Boys
                1 Mile, the runner seeded 4th actually finished 2nd.


        Boys     Boys      Boys     Girls     Girls     Boys    Girls    Boys    Girls
 Seed  1 Mile   2 Mile    5000m(a)  1 Mile    2 Mile     DMR     DMR     4x800   4x800
 ----  ------   ------    --------  ------    ------    ----    -----    -----   -----
  1       1        1         2        1         6         1       2       11       1
  2       3        2         7        4         8         3       1       10       7
  3      22        3         4       11         3         9       9        1       2
  4       2        5         6        2         4         2      10        8       8
  5       6       10        13        8         2         7       4       18      15
  6      19        9        17        6         9        18       6        5      12
  7       4        6         5       13         1        15       5       20       6
  8      12       20        14        3         5         6       8       15       5
  9      11       16        10        7         7         5       3       23       4
 10       9        4         3       12        10         4       7       12      13
 11      15       12        15        9        12        12      11        9      10
 12      16        8        11        5        11        19      12       24       9
 13       8       15         1       10        --        17      15       22      16
 14      10        7        19       --        --        11      14        4       3
 15       7       11        29       --        --        14      16        3      19
 16      17       17         8       --        --        13      17        6      14
 17      13       22        16       --        --        20      18        2      17
 18      14       23         9       --        --         8      13        7      11
 19      18       21        12       --        --        16      --       14      18
 20       5       25        25       --        --        10      --       19      --
 21      23       14        27       --        --        --      --       16      --
 22      21       18        23       --        --        --      --       13      --
 23      20       24        18       --        --        --      --       21      --
 24      --       19        24       --        --        --      --       17      --
 25      --       26        33
 26      --       13        22
                            31
                            28
                            21
                            32
                            34
                            20

(a) 5000m as seeded by 2 Mile times