Starting Position Analysis of Winners in Short Track Speed Skating

Competitions during 2007-2019

Lixin Sun, Kuan Tao, Tianxiao Guo and Fei Liu

School of Sports Engineering, Beijing Sport University, 100084, Beijing, P.R. China

Keywords: Speed Skating, Short Track, Starting Position, Race Analysis, Performance.

Abstract: Short track speed skating is a racing sport on ice, in which contestants compete against each other instead of

the clock. Thus compared to the speed and technical skating ability, equally, if not more important is race

tactics. This study analysed in-depth the starting positions of winners in 121 competitions during 2007-2019,

where 173 female and 247 male champions were announced correspondingly from 4313 female and 5212

male individual races (preliminaries, heats, quarter-finals, semi-finals, and final in 500m, 1000m, 1500m, and

3000m classifications), to explore a pattern of effective tactical positioning strategy. The Kendall’s tau-b (rt)

correlation between starting and finishing position decreases with race distance, which was highest and

positive for all 500m races (0.347, P<0.05), which verified previous studies. Furthermore, starting position

distributions of winners in each round and starting positions variations of champions along the rounds were

analysed. Results show that skaters in the first track were inclined to win the rounds in 500m, 1000m and

1500m (28%, 28% and 22%, respectively) and the differences between starting and finishing positions for

champions were minimized in semi-finals, indicating skaters should spare no effort in semi-final to achieve

success.

1 INTRODUCTION

Short track speed skating is a form of competitive ice

speed skating. In races, competitors are pitched

against each other in groups ranging from four to six

and skate on an oval ice track with a length of 111.12

meters. The races are fast and furious with fastest

speed reaching 91 kilo-meters per hour and skaters

who scramble for advantage regularly come to grief,

often taking their rivals to ground with them.

Furthermore, short track speed skating is a racing

game that tests the speed, technical skating ability,

and aggressiveness of its competitors. Unlike

traditional long-track speed skating, contestants race

against each other instead of the clock, which means

it is how faster you are than you competitors rather

than how fast you really are that will determine your

final positions. To win the competition, strength

quality (specifically defined as strength of leg

muscles contraction) (Felser, 2016), propulsion

(Bullock, 2008), pacing behavior (Noorbergen, 2016;

Menting, 2019; Konings, 2016) and race tactics

(Bullock, 2008, Konings, 2018) are important factors

that coaches and athletes care about. And for race

tactics, the starting position analysis of elite

performance is the first step to acquire an effective

tactical positioning strategy.

According to the special regulations of short track

speed skating from ISU (International Skating

Union), the lane positions of the first qualifying round

of a distance are drawn by the Competitors Steward,

which is a software that can assign the athletes with

random lane numbers and for the subsequent rounds,

the lane positions will be decided by the results from

the preceding qualifying round. More specifically,

athletes who advance to the next round will be

regrouped according to their ranks in the preceding

round and assigned the lane positions from the inside

to the outside of the track by the order of their times

commencing with the fastest time.

A study focused on the influence of starting

position on finishing position in 500m races has

found that there is a significant positive correlation

between them especially in semi-finals and finals

regardless of sexes. This study is based on the data

from 500m races in ISU Short Track World Cups held

over the five seasons from 1999-2000 to 2003-2004

(Maw, 2006). Muehlbauer et al. (Muehlbauer, 2011)

extended that work by studying the relationship

between the starting and finishing positions in all

classifications based on the data from six

106

Sun, L., Tao, K., Guo, T. and Liu, F.

Starting Position Analysis of Winners in Short Track Speed Skating Competitions during 2007-2019.

DOI: 10.5220/0010652700003059

In Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2021), pages 106-110

ISBN: 978-989-758-539-5; ISSN: 2184-3201

Table 1: Pairwise correlation of rounds in different events. P-values are presented in brackets while asterisks indicate that

correlations have significant difference.

500 1000 1500 3000

Preliminaries 0.127** (0.000) 0.080** (0.000) 0.063** (0.004) -

Heats 0.474** (0.000) 0.214** (0.000) 0.090** (0.000) 0.099** (0.000)

Quarter-finals 0.500** (0.000) 0.265** (0.000) 0.154** (0.000) 0.272** (0.000)

Semi-finals 0.465** (0.000) 0.219** (0.000) 0.162** (0.000) 0.397** (0.000)

Final 0.429** (0.000) 0.247** (0.000) 0.168** (0.000) 0.351** (0.000)

All 0.347** (0.000) 0.194** (0.000) 0.133** (0.000) 0.286** (0.000)

competitions during three seasons from 2006-2007 to

2008-2009 and what they have found is that the

strength of correlation between the two positions

decreases with race distance, which is highest and

positive in the 500m races, lowest in the 1500m races

and negative in the 3000m races and shows no sex

difference. A more recent study in 2015 by William

B. Haug et al. (Haug, 2015) also focused on World

Cup 500m races, but was more interested in the

relationship between start performance, which is

measured by rank position entering first corner

(RPEFC) and race outcome in elite athletes. As they

had to use videos get the RPEFC, their data

acquisition was limited by this labor-intensive work.

Although starting position analysis has shown its

prominent role in short track speed skating races, yet

current studies on it seem a little out-of-date with

limited data. This study will first verify the previous

conclusions with new larger data sets, and then focus

on the winners in each round to find out their starting

positions distribution, finally the champion’s starting

positions variations along the rounds are analysed to

examine positioning strategies of this final winners.

2 METHODS

2.1 Data Acquisition

This paper investigated the relationship between the

starting and finishing positions from 121

competitions (World Cup Series / Championships /

Olympic Games) ranging from 2007/08 to 2019/20

season. All data were obtained from the official

website of International Skating Union (ISU). The

original dataset contains 183,158 match information

with 714 female and 904 male athletes. After data

cleaning, which attempted to discard

data when

penalty or disqualification occurred, 67,258 data

points altogether including the positional information

about 500m, 1000m and 1500m competitions in the

preliminary, heat, quarterfinal, semi-final and final

rounds were thus filtered.

2.2 Statistical Analysis

Starting positions were marked as 1 to 4 (500m and

1000m), and 1 to 6 (1500m) that represent inner to

outer lanes. The Kendall’s tau-b (rt) correlation was

analysed to evaluate the correlation between starting

and ending positions during race. The interpretations

of correlation coefficients vary depending on

magnitudes, with values lower than 0.2 or between

0.2 and 0.5 or larger than 0.5, indicating low,

moderate and strong correlations, respectively. All

data were analysed via the SPSS (version 16.0), and

the level of significance was set as 𝑃 < 0.05.

3 RESULTS

Three statistical experiments were conducted

accordingly. (1) We calculated the correlations

between starting and finishing position on the basis of

rounds in all competitions to investigate the overall

impacts of starting lanes on final ranking. (2) Based

on the first part, the starting position distribution of

the winners in each round were analysed. (3)

Dynamical evolution of starting and finishing

position for champions. These sequential

characteristics revealed the strategic patterns of elite

short track speed skating athletes.

3.1 Correlations between Starting and

Finishing Position

Table 1 showed the correlations between starting and

finishing position by different race distances and

rounds. All of these correlations were significant,

with the largest value appearing in the event of 500m

Starting Position Analysis of Winners in Short Track Speed Skating Competitions during 2007-2019

107

Figure 1: Starting position distribution for round winners.

(0.347, 𝑃 < 0.05) and decreasing with progression in

race distance 1000m (0.194, 𝑃 < 0.05) and 1500m

(0.133, 𝑃 < 0.05). 3000m was an exception since the

correlation coefficient is evidently higher that 1000m

and 1500m (0.286, P<0.05). To figure out the

abnormal phenomenon of 3000m, the correlations of

3000m Superfinal and 3000m Relay were calculated,

respectively, the results were shown in Table 2.

3000m Superfinal race displayed the lowest

correlation coefficient in all the race distances (-

0.006, 𝑃 < 0.05), and the high value was contributed

by 3000m Relay (0.281, 𝑃 < 0.05).

icSPORTS 2021 - 9th International Conference on Sport Sciences Research and Technology Support

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Figure 2: Dynamical evolution of starting and finishing position for champions by rounds.

Furthermore, the correlation coefficients by different

rounds showed different tendencies. Such as 500m

column in Table 1, although all the rounds were

positively correlated, the correlation coefficients of

preliminaries were obviously lower than others

(0.127, 𝑃 < 0.05 ), and the similar tendency was

found in 1000m race. But in 1500m and 3000m race,

correlation coefficients of Heats were also far lower

than the final-rounds. By contrast, there was no

specific linear relation about the correlation between

starting and finishing position among quarter-final,

semi-final and final rounds.

This research mainly concentrates on the

individual races, so that we only conduct further

investigation on 500m, 1000m and 1500m races. And

sex was not considered in this research since the

previous related researches drawn no conclusion

about sexual significant difference.

3.2 Starting Position Distribution for

round Winners

Figure 1 showed the starting position distribution of

the winners in each round of the 500m, 1000m and

1500m race. In all three race distances, starting

position 1 had the highest probabilities to be round

winners (28%, 28%, 22%), the narrow margins

suggested that advantages of starting lanes mattered

in some extent. Observing the sub-images of each

race distance, athletes with position 1 possessed an

apparent advantage to win the final rounds (61%,

44%, 30%). On the contrary, in preliminary, heat,

quarterfinal and semi-final rounds, the winners were

mainly distributed in top 3 starting lanes. Skaters in

last few lanes always contributed less winners in all

kinds of race and rounds.

3.3 Dynamical Evolution of Starting

and Finishing Position for

Champions

In order to investigate the performances from

hundreds of champions in every qualifying round, the

dynamical evolvements of mean starting and

finishing positions were calculated in Figure 2. The

blue broken line with square mark represented

starting positions, and the red one with circle

represented finishing positions. The graphs of 500m

and 1000m showed the similar pattern, where mean

starting position and finishing position overlapped on

semi-final. Besides, mean starting positions in all race

distances and qualifying rounds were lower than 3

(out of 4), with mean finishing positions of 500m and

1000m lower than 3 (out of 4) and 1500m lower than

4 (out of 6).

4 DISCUSSION

The purpose of the present study was to determine the

relationship between starting and finishing positions

in championship-level short track speed skating races.

The positive correlations occur in 500m to 3000m

events, which are consistent with findings in [8, 9].

Interesting to note that the magnitude of correlation

decreases by the accumulation of race distances,

which suggests that a change in pacing strategy

occurs depending on race distances. One possible

explanation accounts for such phenomenon as longer

distance is accompanied with more energy

expenditure. For instance, the maintenance of leading

position in 500m requires less energy than during

1000m or 1500m races (Prampero, 1976). In addition,

negative correlation was obtained on superfinals of

3000m. From the energy point of view, it is more

effective and less exhausting to draft than to lead in

prolonged races (Kyle, 1979).

Starting Position Analysis of Winners in Short Track Speed Skating Competitions during 2007-2019

109

Additionally, the starting and finishing positions

are closest in semi-finals for champions, because

competitions in short track speed skating are

elimination races, which means the performance

differences between skaters shrink from preliminary

to final. Elite skaters might adopt a strategy to

conserve energy during qualifying rounds before

semi-finals, however, they must keep excellent

performance to advance to the final round. Besides,

skaters in the first track are inclined to win the rounds

in 500m, 1000m and 1500m (28%, 28% and 22%,

respectively) after computing the mean positions for

winners from preliminary to final qualifying round.

Although starting positions are randomly drawn in

preliminary, faster skaters acquire inner starting

positions compared to slower ones in the subsequent

rounds, which makes it more difficult for opponents

to overtake.

Using artificial intelligence technologies to

visualize and analyse data gains popularity in modern

sports science, due to its outstanding abilities for

generalization and efficiency in investigation of the

nonlinear latent relations between variables. We

acknowledge that some limitations exist in the present

study, such as the involvement of starting and

finishing positions alone instead of incorporating

more detailed information extracted from racing

profiles (i. e. split time). And any disqualifications or

penalties are ruled out during data cleaning process,

which, however, deserves a thorough analysis in the

future work since these accidental events impacts on

the adjustment of racing strategy for skaters.

ACKNOWLEDGEMENTS

This study was supported by grants from the National

Key Research and Development Program of the

Ministry of Science and Technology, China

(2020YFF0304702, 2020YFF0304704).

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