Thread by @JC_rrie

Equalising race distances for men and women in XC - a statistical analysis 📊📈

Preface:
▪️I’m not an expert, just an athlete with nothing better to do
▪️This data was pulled from publicly available sources
▪️This is only a case study, not a comprehensive investigation

CASE STUDY: Scottish National XC Champs 2011-2020 🏴󠁧󠁢󠁳󠁣󠁴󠁿

Reasons for choosing this race:
▪️Encapsulates both mass participation and elite competition in one race
▪️Recently equalised race distances for senior men and women, providing sufficient data pre- and post- distance change

FACTORS BEING CONSIDERED:

1️⃣ Participation
2️⃣ Duration of race (w/ regards to officials & time for slowest runners)
3️⃣ Race excitement (w/ regards to spectators & race for title/medals)
4️⃣ Race quality (w/ regards to participation levels from elite to good club level athletes)

1️⃣ Participation

▫️Pre change average number of finishers:
Men - 538
Women - 231
Total - 769

▪️Post change average number of finishers:
Men - 666
Women - 294
Total - 960

🔄 Change
Men +23.8%
Women +27.3%
Total +24.8%

It might appear as if the change in distance has caused an increase in participation, however if we view the data as a whole we can see there is no significant increase in the upwards trend during the time of the race distance change

There appears to be a significant increase in participation in 2019, which could be attributed to the distance change with a lag effect, but due to the decrease in 2020, it seems more likely this was due to other external factors.

2️⃣ Race duration

▫️Pre change average time of slowest 5 runners
Men - 74:20
Women - 49:58
Total - 124:18

▪️Post change average number of finishers:
Men - 69:58
Women - 71:51
Total - 141:49

🔄 Change
Men -5.87%
Women + 43.8%
Total +14.1%

🔻As we can see the decrease in race distance for men has limited effect on the race duration.

🔺The distance increase for women has greatly increased the race duration, affecting the length of the schedule and the amount of time officials are required to be out on the course

3️⃣ Race excitement

For this factor, I have analysed the spread of the top 10 athletes in each race, as the closer this is the more exciting it is for the spectators.

Range, standard deviation

▫️Pre change top 10 spread
Men - 1:51, 36.3s
Women - 2:06, 41.4s

▪️Post change too 10 spread:
Men - 1:44, 32.4
Women - 2:35, 54.6

🔄 Change
Men -7s, -3.9s
Women +29s, +13.2s

🔻The distance decrease for men has marginally decreased the spread of the top 10

🔺The distance increase for women has significantly spread the top 10, reducing the excitement of the challenge for the title and medals

4️⃣ Race quality

For this factor I have analysed the spread of the top 50, top 100 and the entire field.

💯 Top 50/100 spread can show us the difference in quality between the leaders and high level finishers

➕Total spread can show us the quality of the entire field

💯 top 50 & top 100 range

▫️Pre change:
Men - 4:59, 7:15
Women - 5:18, 7:55

▪️Post change
Men - 4:05, 5:43
Women - 6:53, 10:42

🔄 Change
Men -18.1%, -21.1%
Women +29.9%, +35.2%

🔻The decrease in race distance for men brings the top 50/100 significantly closer together

🔺The increase in race distance for women’s takes the top 50/100 significantly further apart

👫➖
This is obvious due to the change in race duration, but it is worth noting that the change has also made the spreads less equal between men and women

➕Total field spread
(standard deviation and interquartile range)

▫️Pre change (sd, iqr):
Men - 6:44, 8:58
Women - 4:34, 6:18

▪️Post change (sd, iqr)
Men - 6:34, 8:53
Women - 7:05, 10:10

🔄 Change
Men -2.46, -0.9%
Women +55.1%, +61.4%

🔻 The decrease in distance for men has had minimal effect on the total spread of the field

🔺The increase in distance for women has significantly spread the entire field out.

👫➕
It is worth noting that the change in distances has made the spread of the entire field more equal between men and women

Conclusion ☑️

In this case study, the equalising of race distances has been shown to:
▪️Have little effect on participation levels
▪️Increase event duration for officials
▪️Reduce equality in the spread of the top 50/100
▪️Increase equality in the spread of the entire field

Further considerations ❓

What this study does not consider:
▪️How does this affect age groups other than senior?
▪️How does this affect the athletes’ transition from junior to senior and retention levels through the age groups?
▪️Is this data replicated in other events?

📙 Closing remarks:

This was not meant to provide a solution, and I am not qualified nor in a position to make this decision, it is meant to provide insight & evidence into the effects the decision may have.

Thanks for the inspiration & help with the data/analysis @CordyParker

https://twitter.com/cordyparker/status/1352259722108395521

@JoannaCoates @BritAthletics @UKA_AC @EnglandRunning @scotathletics @WelshAthletics #ukrunchat