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Age Grading

Comparing times across age groups

David Nordstrom | March 1, 2006

Two recent articles, Swimming World’s “Holding Back the Years” by Phillip Whitten, March 2005; and USMS SWIMMER’s “Records Topple at USMS Short Course Nationals in Fort Lauderdale”, July – August 2005, prompted me to attempt to further quantify performances vs. age.  The running community has an age-grading scheme that allows runners in any age group to “adjust” their times to another age group.  So if you are a 70 year old, you can use a formula to find out what your current time would be as a 25 year old with the age adjustment.  In some road races, awards are given to best equivalent times ( a 70 year old with a 25 min 5K beats the 25 year old with a 22 min 5K).  As far as I know, we swimmers don’t have an age grading system.  This is an attempt to develop one.

The articles mentioned above have to do with general population vs Masters’ expected yearly decline in performance.  The general rule is that the overall population declines at approximately 1% per year after age 25 for about 40 years.  Then the rate of decline increases.  The article showed that Masters swimmers did much better than that.  The USMS Swimmer’s article featured – in part – Richard Abrahams, who showed that a life time best at age 60 (24.46 – 50 yd fly) completely destroys the decline prediction graph.

So what is going on here?  A 60 year old man going 49.14 in the 100 free?  Now THAT’S not normal, Richard!  But we can get a feel for what “normal” is for Masters swimmers by looking at results.  What I looked at were the 5th place times on the Top Ten list for 2004.  (At the time, 2005 results were not complete).  Why 5th place?  Because there are always a few “Richard Abrahams” at the top of every age group that are not at all “normal” – even for Masters.  I used the 5th place time in every age group for every event for both women and men to compute a ratio using 1.0000 for the fastest time.  Example:  the fastest 5th place time in the women’s 100 free was 53.61 in the 25 – 29 age group.  That time has a value of 1.0000.  In the 55 – 59 age group the 5th place time was 1:06.62 or .8047 as fast as 53.61.  So if you went 1:06.62 as a 58 year old, the equivalent time for a 28 year old is 53.61 – according to actual performances in the national top 10 in 2004.  Conversely, if you went 53.61 as a 28 year old, your equivalent time as a 58 year old is …1:06.62.  There were 12 age groups with a completed top 10 list for women and 13 age groups with full listings for men.  Since there are 18 individual events, there are 450 comparison ratios in the table.

The purpose of age grading is for motivation – what does your time as a 58 year old mean?  How fast is that swim if I were 28?  or 78?  You can compute your equivalent time for any age – even compare your times now as a 58 year old with your times in college.  Hopefully, even though you are getting slower, you’ll see that your age graded “adjustment” shows you’re doing pretty well – especially as compared to the general population.

To calculate your age graded time for any event:

1. Divide the 4 digit multiplier in your age group by the 4 digit multiplier in the age group for which you want to see your equivalent time.

2. Multiply the result of step 1 by your current time. 

This will give you the age graded equivalent time for the other age group.

That’s it.  It works in all 450 cases.  It’s based on factual 2004 data.  The ratio tables will change in the future based on new data; but, for now, you will be using the actual current (2004) data to compare performances.  (And keep in mind that Masters performance data is far superior to what you can expect from the general population.)

The system isn’t perfect.  As stated earlier, many more swimmers are competing for that 5th place in the 19 – 49 age groups than in the 50+ age groups.  But as time marches on, the youngsters will get old and the participation in all age groups will be a lot closer to equal.  Therefore, the validity of the ratios will increase with time – as long as the data tables are upgraded periodically.  (Since we are starting with 2004, perhaps every 4 years – every Olympiad – would be appropriate.)   The ratios are not perfect.  But they are a lot better than guessing; and guessing is all we have at present.

Just wait.  In 30 years, the 70 year olds will be blowing the doors off today’s 70 – 74 age group records.  The 70 year olds may be faster than today’s 50 year olds.  Why?   Let’s compare today’s 40 year old with today’s 70 year old.  Today’s 40 year old was likely a high school senior swimmer in 1983.  The 70 year old was a high school senior in 1953.  How many high school and age group teams were there in 1953 compared to 1983?  How about today’s 80 year old?  Do you think he/she was competing for a good high school swimming team during WWII in 1943?  All the swimmers that are 65 or older today had drastically fewer opportunities in their youth to build a good technical foundation for lifetime competition in swimming.  The ratio tables of the future will look nothing like today's tables.  We will see some REALLY fast 70+’s by 2035.  Phillip Whitten illustrated that the drop-off rate doesn’t get to the “normal” 1%/yr until age 70.  (And by age 70, the drop-off rate for non-athletes is much higher than 1%).  I predict that the drop-off rate in the future will never get to 1% for Masters swimmers.

The average age for women’s top performance was 28.5; for men, 29.7.  But the biggest difference in gender was the diversity within each sex.  Virtually all of the men’s top performances were within the 25 – 29 age group.  For women it was nearly evenly split between the 19 – 24, 25 – 29, and 35 – 39 age groups.  There were no women’s top times in the 30 – 34 age group.  The women actually peaked at the 35 – 39 range before showing a near linear decline.  The men stayed nearly level until the 40 – 44 age group before starting a steady decline.  Starting nearly even at the 40 –44 age groups, the women then declined more than the men.  This likely reflects fewer opportunities in the past for women to be involved in learning the skills of the sport.

The future of Masters swimming will look nothing like the  present.  As stated earlier, as today’s baby boomers age up; the competition opportunities of their youth will show up as very fast times compared with today’s older age groups.  Abrahams’ 49.14 in the 100 free as a 60 year old is just a preview of things to come!

This statistical analysis is informal and imperfect.  It is an early attempt to quantify tends in performance vs. age.  Hopefully, some of you with expertise in this type of research will refine this analysis to help add to the body of knowledge about aging.  Perhaps every 4 years (Olympiads) we can update the data and see what happens.  I strongly believe that the future data will demonstrate that aging doesn’t have to lead to nearly as much decline as “normal”.

Women – Ratios

 

 

19-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-79

Free

50

.9883

1.0000

.9685

.9731

.9891

.9421

.9076

.8165

.7812

.7253

.6489

.6155

Free

100

.9795

1.0000

.9976

.9891

.9849

.9361

.8892

.8047

.7447

.7223

.6240

.5703

Free

200

.9839

.9781

.9515

1.0000

.9553

.9105

.8748

.7941

.7143

.6967

.6246

.5593

Free

500

.9980

.9857

.9670

1.0000

.9680

.9293

.8956

.8232

.7218

.6995

.6480

.5755

Free

1000

.9305

.9243

.9548

1.0000

.9383

.9239

.8569

.8084

.7000

.6873

.6162

.5414

Free

1650

.9592

.9459

.9672

1.0000

.9665

.9265

.8500

.8327

.6982

.6929

.6129

.5247

Back

50

1.0000

.9893

.9930

.9882

.9665

.9410

.8741

.7950

.7438

.6841

.6128

.5711

Back

100

1.0000

.9937

.9923

.9992

.9514

.9283

.8681

.7825

.7221

.6789

.5972

.5515

Back

200

.9969

.9879

.9778

1.0000

.9603

.9175

.8670

.7913

.7067

.6847

.6181

.5421

Br.

50

1.0000

.9683

.9754

.9615

.9595

.9407

.8484

.8339

.7528

.6838

.6584

.5550

Br.

100

1.0000

.9929

.9764

.9952

.9719

.9445

.8694

.8402

.7372

.6979

.6612

.5677

Br.

200

1.0000

.9794

.9696

.9918

.9619

.9408

.8623

.8194

.7374

.6805

.6553

.5654

Fly

50

.9784

1.0000

.9802

.9653

.9845

.9207

.8977

.7998

.7150

.6494

.5726

.5072

Fly

100

.9603

1.0000

.9750

.9813

.9666

.8910

.8582

.7135

.6503

.6089

.5135

.4214

Fly

200

1.0000

.9888

.9633

.9938

.9388

.9169

.7755

.7164

.6515

.5688

.4876

.4339

IM

100

.9890

1.0000

.9673

.9761

.9671

.9176

.8587

.7992

.7397

.6910

.5856

.5007

IM

200

.9772

.9908

.9630

1.0000

.9477

.9051

.8323

.7798

.7216

.6635

.6031

.5261

IM

400

1.0000

.9824

.9560

.9886

.9501

.9060

.8218

.7685

.6842

.6258

.6110

.4395

 

Avg

.9856

.9838

.9720

.9891

.9627

.9244

.8615

.7955

.7179

.6745

.6084

.5316

 

Men – Ratios

 

 

19-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-79

80-84

Free

50

.9586

1.0000

.9604

.9564

.9387

.9266

.9053

.8720

.8189

.7776

.7390

.6478

.5743

Free

100

.9556

.9989

1.0000

.9580

.9381

.9247

.9076

.8786

.8043

.7582

.7117

.6155

.5485

Free

200

.9743

1.0000

.9918

.9928

.9822

.9328

.9331

.8816

.8206

.7403

.7023

.6093

.5275

Free

500

.9709

.9817

.9839

1.0000

.9909

.9350

.9393

.8645

.8181

.7736

.7223

.5871

.4948

Free

1000

.9944

.9695

.9834

.9945

1.0000

.9827

.9592

.9089

.8128

.7918

.7148

.5851

.4609

Free

1650

.9454

.9446

.9694

1.0000

.9808

.9564

.9479

.8730

.8080

.7756

.7133

.5952

.4644

Back

50

.9608

1.0000

.9748

.9729

.9571

.9257

.9031

.8404

.8244

.7525

.7012

.6146

.5670

Back

100

.9564

1.0000

.9801

.9459

.9464

.9157

.8885

.8251

.7812

.7006

.6850

.6145

.5219

Back

200

.9977

1.0000

.9991

.9821

.9890

.9577

.9251

.8566

.8087

.7211

.7172

.5793

.5369

Br.

50

.9753

1.0000

.9788

.9913

.9743

.9542

.8906

.8749

.8244

.7593

.7458

.6605

.5539

Br.

100

.9897

1.0000

.9747

.9840

.9850

.9443

.8849

.8661

.8019

.7581

.7073

.6271

.5167

Br.

200

.9653

1.0000

.9469

.9885

.9659

.9524

.9025

.8750

.8240

.7238

.6804

.6268

.4660

Fly

50

.9547

1.0000

.9685

.9491

.9507

.9229

.8992

.8656

.8308

.7565

.7084

.5682

.4828

Fly

100

.9513

1.0000

.9687

.9565

.9665

.9275

.9088

.8453

.7808

.6766

.6382

.5162

.3588

Fly

200

.9142

1.0000

.9437

.9811

.9626

.9154

.9013

.7984

.7179

.6395

.5827

.4453

.3125

IM

100

.9581

1.0000

.9782

.9508

.9743

.9231

.9067

.8517

.8065

.7392

.7071

.5971

.5166

IM

200

.9468

1.0000

.9741

.9551

.9775

.9146

.8995

.8459

.7841

.7035

.6675

.5903

.4552

IM

400

.9771

1.0000

.9585

.9775

.9658

.9262

.9158

.8564

.7621

.6880

.6461

.5510

.3877

 

Avg

.9637

.9942

.9742

.9743

.9692

.9354

.9121

.8600

.8016

.7353

.6939

.5906

.4859

To calculate your age graded time for any event:

1. Divide the 4 digit multiplier in your age group by the 4-digit multiplied in the age group for which you want to see your equivalent time.

2. Multiply the result of step 1 by your current time. This will give you the age graded equivalent time for the other agegroup.

This month's article was submitted by Masters swimmer David Nordstrom, a retired high school science teacher and swim coach. Nordstrom coached age group and high school swimmers for 30 years and has been coaching Masters swimmers for the last 3 years. He is a member of the Alamo Area Aquatics Association (AAAA) in San Antonio, Texas.

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