Stats for ladies from 2008-09 season

[poorScorer]

Step

4th stat for ladies is about STEP.

I limited this list to ladies with more than 4 marks only.
'Level3' column shows how many Level3 mark she got out of total tries.
For example, Mao, Yu-Na, Joannie got Level3 mark 10 times out of 10.

POINT ( max ) | GOE ( max )__ | Level3 | Name
4.110 ( 4.30 ) | +0.810 ( 1.0 ) | 10/10 | Mao ASADA
4.030 ( 4.30 ) | +0.730 ( 1.0 ) | 10/10 | Yu-Na KIM
3.980 ( 4.20 ) | +0.680 ( 0.9 ) | 10/10 | Joannie ROCHETTE
3.925 ( 4.00 ) | +0.625 ( 0.7 ) | 4/4 | Akiko SUZUKI
3.825 ( 3.90 ) | +0.525 ( 0.6 ) | 8/8 | Fumie SUGURI
3.750 ( 4.20 ) | +0.650 ( 0.9 ) | 8/10 | Carolina KOSTNER
3.750 ( 4.00 ) | +0.450 ( 0.7 ) | 8/8 | Cynthia PHANEUF
3.750 ( 3.90 ) | +0.450 ( 0.6 ) | 4/4 | Sarah MEIER
3.700 ( 3.80 ) | +0.400 ( 0.5 ) | 4/4 | Ashley WAGNER
3.625 ( 3.90 ) | +0.450 ( 0.6 ) | 7/8 | Alissa CZISNY
3.410 ( 4.00 ) | +0.235 ( 0.7 ) | 7/8 | Miki ANDO
3.400 ( 3.70 ) | +0.350 ( 0.5 ) | 3/4 | Beatrisa LIANG
3.375 ( 3.80 ) | +0.325 ( 0.5 ) | 6/8 | Rachael FLATT
3.243 ( 3.80 ) | +0.318 ( 0.6 ) | 5/8 | Laura LEPISTO
3.217 ( 3.80 ) | +0.333 ( 0.5 ) | 4/6 | Tugba KARADEMIR
3.200 ( 3.80 ) | +0.233 ( 0.5 ) | 4/6 | Yukari NAKANO
3.125 ( 3.80 ) | +0.325 ( 0.5 ) | 2/4 | Kimmie MEISSNER
3.075 ( 3.80 ) | +0.275 ( 0.5 ) | 2/4 | Julia SEBESTYEN
3.075 ( 3.60 ) | +0.150 ( 0.3 ) | 5/8 | Susanna POYKIO
2.904 ( 3.90 ) | +0.304 ( 0.7 ) | 2/5 | Elene GEDEVANISHVILI
2.865 ( 3.50 ) | +0.065 ( 0.2 ) | 2/4 | Ivana REITMAYEROVA
2.850 ( 3.50 ) | +0.050 ( 0.2 ) | 2/4 | Ana Cecilia CANTU
2.850 ( 3.40 ) | +0.113 ( 0.4 ) | 4/8 | Elena GLEBOVA
2.826 ( 3.90 ) | +0.240 ( 0.6 ) | 2/7 | Anastasia GIMAZETDINOVA
2.805 ( 3.80 ) | +0.005 ( 0.5 ) | 2/4 | Mirai NAGASU
2.750 ( 3.80 ) | +0.283 ( 0.5 ) | 1/6 | Caroline ZHANG
2.725 ( 3.30 ) | -0.075 ( 0.0 ) | 2/4 | Kerstin FRANK
2.700 ( 3.80 ) | +0.213 ( 0.5 ) | 2/8 | Alena LEONOVA
2.683 ( 3.60 ) | +0.133 ( 0.3 ) | 2/6 | Jenna MCCORKELL
2.575 ( 3.80 ) | +0.213 ( 0.5 ) | 2/8 | Annette DYTRT
2.445 ( 3.40 ) | +0.020 ( 0.1 ) | 1/4 | Katarina GERBOLDT
2.420 ( 3.40 ) | -0.023 ( 0.1 ) | 1/7 | Yan LIU
2.350 ( 2.40 ) | +0.050 ( 0.1 ) | 0/6 | Candice DIDIER
2.325 ( 2.40 ) | +0.025 ( 0.1 ) | 0/4 | Katrina HACKER
2.283 ( 2.50 ) | +0.067 ( 0.2 ) | 0/6 | Binshu XU
2.168 ( 2.30 ) | -0.008 ( 0.0 ) | 0/8 | Na-Young KIM
2.050 ( 2.30 ) | +0.000 ( 0.0 ) | 0/4 | Mira LEUNG
2.050 ( 2.30 ) | +0.000 ( 0.0 ) | 0/4 | Yueren WANG

 

[enlight78]

The American skaters seem to be very strong in spirals and spins but weaker in jumps and steps.Mao asada problem all season has been fullfilling the requirements for her spiral and spins. And it really reflected in the stats. She should really work on that. And I must agree Mao had the best step sequence follow by Yu-Na the Joannie. I am loving these stats.

 

[fairly4]

poor scorer--thank you
1) do you have a day job--why--i do numbers at night and I know it takes a very long time-so the list you complied---Great job, Thank you for Your Long Hours at work for this.
it takes time to comply the list --than to write it, Thank you-
So i think this means average scores on jumps, steps and so-forth.
without the downgrades or negative Goes--is that correct.

 

[poorScorer]

fairly4, It doesnt take that long as you might think.
I wrote small library and routine which extracts data from pdf and make them into DB.
However, Yes, it does take some time to check the fact and formatting text back.
I tried to use HTML table but vBulletin doesnt allow me to do so. urgh...

So i think this means average scores on jumps, steps and so-forth.
without the downgrades or negative Goes--is that correct.

umm... a score sums up all the things you mentioned here. doesn't it?
Reason why I attached GOE next to score is just for information.

Anyway, thanx for reading and commenting.

 

[Wicked]

So informative to see the elements laid out like this. It surprises me that Tugba Karademir is ranking so high on many of these and Kimmie so low. But I guess figures don't lie.

 

[hurrah]

So informative to see the elements laid out like this. It surprises me that Tugba Karademir is ranking so high on many of these and Kimmie so low. But I guess figures don't lie.

Numbers may not tell lies but they don't necessary tell truths either. These figures just show who was given the most points for doing whatever element that is being scored according to the judgement system in place.

 

[Wrlmy]

So Alissa was the best American lady in spin and spiral and the second best in step! This again shows all she has to do is land the jumps! Thank you for the list poorscorer. This is really informative and also makes sense. Perhaps you could also come up with the stats for the pcs please?

 

[poorScorer]

Jump Composition

My 5th stat for ladies tackles on 'Jump Composition'.

Jump composition? what is that?
It counts every jump she executed on the ice and classify them by 6 major Categories, that is A, F, Lo, Lz, S, T.
So, it goes like this.
Let's say a skater did 2A. Easy, I add +1 to 'A' category.
Combo like 3Lz+2T? No problem, I add +1 to 'Lz', and then +1 to 'T'.

I didn't take into account things like fall or downgrade.
The only thing matters here is that she actually tried that jump in competiton.

I tried to find each skater's jump preference here.
If you aren't sure you can land that jump, you just take that off your program, right?
So I think this can show her preference, or possible weak spot.

Basic methods are same as other stats.
I've grabbed data from 10 intl. competitions last season,
and listed here only skater whose total jump count exceeds 20.

I put percentage numbers here.
Let's take Joannie for example.
Of all the 71 jumps she did, 15 of them were axel. So, 21.13% goes to 'A' column.

Sorting standard is 'lower-deviation-first', that is , You know, 'how evenly distributed'.
Joannie is top here because she is the only lady that no jump below 10% ,and none above 25%.
The more I see her, she looks more all-round, solid, balanced skater.

A (%) | F (%) | Lo (%)| Lz(%)| S (%) | T (%) | Name
21.13 | 14.08 | 12.68 | 21.13 | 12.68 | 18.31 | Joannie ROCHETTE
16.67 | 20.00 | 16.67 | 20.00 | 06.67 | 20.00 | Rachael FLATT
17.86 | 14.29 | 07.14 | 21.43 | 14.29 | 25.00 | Julia SEBESTYEN
20.27 | 20.27 | 14.86 | 13.51 | 06.76 | 24.32 | Carolina KOSTNER
24.14 | 13.79 | 20.69 | 20.69 | 06.90 | 13.79 | Akiko SUZUKI
24.00 | 12.00 | 12.00 | 24.00 | 08.00 | 20.00 | Kimmie MEISSNER
22.22 | 18.52 | 11.11 | 14.81 | 07.41 | 25.93 | Katarina GERBOLDT
16.67 | 20.83 | 25.00 | 20.83 | 08.33 | 08.33 | Ashley WAGNER
17.86 | 21.43 | 14.29 | 17.86 | 03.57 | 25.00 | Mirai NAGASU
17.78 | 08.89 | 13.33 | 15.56 | 13.33 | 31.11 | Yan LIU
20.69 | 20.69 | 24.14 | 20.69 | 06.90 | 06.90 | Mira LEUNG
21.43 | 25.00 | 07.14 | 17.86 | 07.14 | 21.43 | Ana Cecilia CANTU
22.22 | 11.11 | 03.70 | 22.22 | 14.81 | 25.93 | Sarah MEIER
23.68 | 15.79 | 07.89 | 15.79 | 07.89 | 28.95 | Binshu XU
24.32 | 13.51 | 08.11 | 20.27 | 06.76 | 27.03 | Yu-Na KIM
20.00 | 20.00 | 15.00 | 06.67 | 08.33 | 30.00 | Alena LEONOVA
15.38 | 11.54 | 11.54 | 23.08 | 07.69 | 30.77 | Cynthia PHANEUF
13.33 | 20.00 | 26.67 | 06.67 | 06.67 | 26.67 | Caroline ZHANG
20.00 | 20.00 | 06.67 | 13.33 | 06.67 | 33.33 | Yukari NAKANO
17.24 | 12.07 | 34.48 | 20.69 | 06.90 | 08.62 | Miki ANDO
26.76 | 21.13 | 29.58 | 07.04 | 04.23 | 11.27 | Mao ASADA
23.53 | 23.53 | 00.00 | 23.53 | 05.88 | 23.53 | Fumie SUGURI
20.00 | 10.00 | 00.00 | 15.00 | 25.00 | 30.00 | Anastasia GIMAZETDINOVA
26.92 | 23.08 | 00.00 | 23.08 | 05.77 | 21.15 | Na-Young KIM
23.08 | 15.38 | 07.69 | 00.00 | 23.08 | 30.77 | Annette DYTRT
15.38 | 23.08 | 07.69 | 23.08 | 00.00 | 30.77 | Beatrisa LIANG
26.92 | 15.38 | 07.69 | 00.00 | 19.23 | 30.77 | Yueren WANG
22.22 | 14.81 | 07.41 | 22.22 | 00.00 | 33.33 | Alissa CZISNY
14.81 | 18.52 | 05.56 | 14.81 | 07.41 | 38.89 | Susanna POYKIO
36.36 | 00.00 | 18.18 | 09.09 | 18.18 | 18.18 | Kerstin FRANK
25.64 | 20.51 | 05.13 | 15.38 | 00.00 | 33.33 | Jenna MCCORKELL
23.53 | 02.94 | 00.00 | 17.65 | 14.71 | 41.18 | Elene GEDEVANISHVILI
28.95 | 07.89 | 02.63 | 18.42 | 02.63 | 39.47 | Candice DIDIER
17.54 | 00.00 | 21.05 | 07.02 | 10.53 | 43.86 | Laura LEPISTO
21.95 | 12.20 | 00.00 | 02.44 | 21.95 | 41.46 | Tugba KARADEMIR
20.00 | 00.00 | 26.67 | 00.00 | 13.33 | 40.00 | Katrina HACKER
27.59 | 00.00 | 06.90 | 05.17 | 18.97 | 41.38 | Elena GLEBOVA
23.08 | 03.85 | 07.69 | 00.00 | 23.08 | 42.31 | Ivana REITMAYEROVA

 

[hurrah]

PoorScorer,

You're fantastic! But if you could separate out double jumps from triple jumps, I would find it more reflective of the skater's jumping skills. Also, downgrades and GOEs also need to be taken into account within the same analytical framework.

 

[ae9177]

OMG PoorScorer, I truely admire you! Fantastic analysis, which provided so much interesting information.

How did you get this done? Are you keeping track all the protocols after each competition or you have an automatic system to imput and analyze all the data? Either way, that's huge amount of work, I really appreciate your effort.

I'm surprised to see Mao's salchow percentage is so low, I thought that's one of her strongest jumps.

 

[museksk8r]

I'm surprised to see Mao's salchow percentage is so low, I thought that's one of her strongest jumps.

Really? Mao very rarely attempts a 3Salchow in competition. That's why her percentage is so low for that element. I've only seen her land it twice in competition cleanly, and that was at last season's NHK Trophy and Grand Prix Final. She singled it and fell at Trophee Eric Bompard and didn't even attempt it at 4CC, Worlds, and the World Team Trophy.

 

[coconutpunch]

Maybe ae9177 meant to say the loop...?

 

[jjane45]

Jump composition comparison is awesome!! Great job again

 

[poorScorer]

if you could separate out double jumps from triple jumps, I would find it more reflective of the skater's jumping skills. Also, downgrades and GOEs also need to be taken into account within the same analytical framework.

Thanx for your comment. Yes, I can separate them.
But I'm little bit doubtful how informative or interesting it would be.
You know, DGs, GOEs, Revolution ... all those things summed into 'score' after all.
But I made a table for 'jump scores' part already, as first stat in this thread.
Can I make any more interesting stat for jumps? I'm not sure about that.

But I would certainly chew on this later.
If you have better idea, feel free to tell me about that.
Thank you.

 

[hurrah]

Thanx for your comment. Yes, I can separate them.
But I'm little bit doubtful how informative or interesting it would be.
You know, DGs, GOEs, Revolution ... all those things summed into 'score' after all.
But I made a table for 'jump scores' part already, as first stat in this thread.
Can I make any more interesting stat for jumps? I'm not sure about that.

Thank you poorScorer---you really should change your name!

Separating out the double jumps and triple jumps and measuring the skater's triple jump diversity will enable us to assess if skaters would be scored differently if a new judging protocol to award skaters for being able to jump all 5 triples were to be adopted.

Examining DGs and GOEs is interesting because it enables us to see what exactly judges see as being worthy of positive/negative GOEs. For example, there may be some skaters who are awarded positive GOEs despite getting wrong-edge calls or underrotation, and vice versa. Is it the position in the air? Is it the distance/height that influences GOEs? Is it the entry speed? Is it the flow out of the jump? It would be interesting to examine this.