What Will It Take To Score At Women’s NCAAs?

2025 NCAA Division I Women’s Swimming and Diving Championships

• March 19-22, 2025
• Weyerhaeuser King County Aquatics Center — Federal Way, Washington
• Short Course Yards (25 yards)
• Start Times: Prelims: 10 AM ׀ Finals: 6 PM (Pacific Daylight Time)
• Meet Central
• Official Psych Sheets
• SwimSwam Preview Index
• Live Results
• Live Stream

Predicting what it will take to score (ie top-8 and top-16 in prelims) in each event at NCAAs can seem a little like black magic. Events go through periods of strength and weakness, consistency and inconsistency. External factors can have an effect too – remember when the breaststroke events at the Paris Olympics were predicted to be among the fastest in history?

With that in mind we’ve built a simple model to predict the prelims results for NCAAs this year. A good predictions model should be based on the psych sheets – no matter how an event has been in previous years, how quick it is this year will depend on who’s entered. Year on year predictions are great for identifying and analysing trends, but won’t be the best for individual years.

Our model should be able to answer (among others) this question: given a 16th seed of 22.20 in the 50 freestyle, what does it take to finish 16th and score, and answer just as well if the 16th seed is a 22.50?

When talking seed position here, we are only including swimmers that finished the race legally. Therefore any swimmers with a DQ or DFS were taken out entirely for that event.

What’s The Data, Mr Wolf?

The core data used to make the model is the NCAA results from the past 10 championships (2014-2024). Within that, the model treats every individual position/event combination separately.

Why do we make the model do this? It’s true that by massively increasing the number of datasets, we slash the number of samples in each dataset by the same factor. However, what happens down at seed #30 won’t be the same as what happens up at seed #3. Whilst the aim at both is to try to make a final, there’s almost a necessity to drop time to do so if you’re starting from lower down.

If each sample were to include the result for every seed in an event over the 10 years, we wouldn’t be predicting the change from seed time to prelims time for each position – we’d be predicting how the average time at all seed positions changes, and then applying that prediction to every seed.

Instead, the supervised Machine-Learning model we’ve built will predict the time for each position independently of any other position. As an example, for position #8, we predict the time based on the time from the psych sheets for seed #8 and what the relationship between seed #8’s time and prelims finisher #8’s time has been in the training date (2014-2024).

With all that in mind we have the following predictions for this year’s prelims. We’ll take a look at how well the model does after the championships.

The model does predict the prelims times for every position, but we’re only including some of the most important in the table here. You can see the full set of predictions (1-50) here

2025 Predictions