Who Got Faster? Improvement at Women’s D1 Conference Meets

For most of the college swimming world, championship season is over. Team’s conference meets marked the pinnacle of their seasons. While those meets were happening, we covered the team battles and individual winner extensively. But many teams aren’t in a position to contend for a conference title. Many swimmers will never win a conference individual title.

A big part of how those swimmers define success is time. Did I go faster? Was this a best time? That’s something we can measure.

Methodology

To get an idea of team’s performance compared to their own previous best times, I grabbed every conference and nationals time from the last 4 years. I then compared a swimmer’s best time from an event at their conference meet this year to their best time in that event from previous year’s conference or nationals meets.

I limited the previous year’s data to conference and nationals because I wanted a guarantee that the only times that I compared to were tapered times in “on” events. A swimmer shouldn’t get credit for a 1 minute improvement in the mile if their only previous mile time was last year at a dual meet. By excluding non championship meets we can avoid that problem entirely.

The downside of this approach is that freshmen improvements aren’t included in the analysis at all. (and yes I know, it would be much better to have them. Adding that in makes this analysis orders of magnitude harder). Also it eliminates possible mid season taper PRs from the baseline data. (that’s more negligible, but with team’s different rest levels mid season, it seemed like a confounding variable I didn’t want to have to consider)

There are a few teams that likely haven’t fully rested yet. The Stanford women, for example. For them this analysis isn’t very useful. Their target meet is NCAA’s. However for the vast majority of division 1, that isn’t the case. Schools with only a couple of qualifiers are unlikely to see their numbers change significantly with the inclusion of nationals.

Results

There were 6533 swims at women’s conference meets where the swimmer had a time in that event from a previous conference or nationals meet. Times were a median of .1% slower than previous season times. They were an average of .2% slower and the time change percentages had a standard deviation of 1.8%. Here’s the distribution of time changes:

Ohio led the way with median time drop of 1.2% on 42 swims. LSU were the top major conference team also with a median time change of 1.2% improvement. LSU had the highest proportion of swimmers that improved as 86% of their swimmers were faster. VMI and Holy Cross also had median improvements of 1.2%.

The Texas women were the second worst performing major conference team (median time add of .8%, only Nebraska was worse among power conference teams). With the weakness of their conference and with how many of their swimmers secured qualification before the conference season started, this probably will improve quite a bit once nationals times are included.

If we’re looking for clues about nationals, the Tennessee women jump out. They swam really well at SEC’s. They dropped a median of .9% on 35 swims. That would indicate they were all out at SECs, and probably don’t have much time left to drop at nationals. They are 4th on the scored psych sheet, so it will be worth watching if they can hold onto that position.

Every team in the division’s time changes are in the table below. If you want last year’s data for this metric that can be found here.

All Teams Data

Negative is faster. Positive is slower.

  Median Change Average Change Number of Times % that were Faster
Ohio -1.2% -1.3% 42 76%
LSU -1.2% -1.0% 37 86%
Virginia MI -1.2% -1.0% 13 77%
Holy Cross -1.2% -0.9% 30 67%
Buffalo -1.0% -1.1% 37 78%
Tennessee -0.9% -0.6% 35 57%
Duke -0.8% -0.6% 18 72%
Hawaii -0.8% -0.3% 36 67%
New Hampshire -0.8% -1.1% 20 80%
South Carolina -0.8% -0.5% 25 68%
American -0.7% -0.4% 24 71%
Fresno State -0.7% -0.6% 46 65%
Florida -0.7% -0.7% 34 82%
Auburn -0.7% -0.8% 37 76%
Northern Ariz -0.7% -0.7% 45 67%
Monmouth -0.7% -0.7% 31 61%
Eastern Mich -0.7% -0.6% 47 77%
Pepperdine -0.6% -0.8% 40 65%
Bowling Green -0.6% -0.1% 36 67%
Lafayette -0.6% -0.3% 8 63%
UN Omaha -0.6% -0.3% 32 59%
Iowa State -0.6% -0.6% 40 75%
Richmond -0.5% 0.2% 23 61%
Indiana -0.5% -0.7% 38 66%
Central Conn St -0.5% -0.7% 27 67%
Fairfield -0.5% -0.1% 33 55%
Florida St -0.5% -0.6% 23 74%
Incarnate Word -0.5% 0.3% 29 55%
Toledo -0.4% -0.2% 30 53%
Providence -0.4% -0.4% 50 58%
James Madison -0.4% -0.7% 29 69%
Tulane -0.4% -0.4% 33 70%
U.S. Navy -0.4% -0.3% 29 69%
Boston College -0.4% -0.4% 29 72%
San Jose St -0.4% -0.2% 38 61%
Houston -0.4% -0.3% 45 60%
Ohio St -0.4% -0.5% 48 63%
Arkansas -0.3% -0.1% 23 61%
Cornell -0.3% -0.1% 34 62%
Penn St -0.3% 0.0% 27 56%
San Diego St -0.3% -0.1% 30 60%
Towson -0.3% -0.4% 38 55%
Grand Canyon -0.3% 0.6% 13 62%
Northern Colo -0.3% -0.2% 19 58%
NC State -0.3% -0.3% 36 56%
Boise St -0.3% -0.5% 50 58%
Miami Ohio -0.3% -0.2% 32 66%
Siena -0.3% 0.4% 35 57%
Mt St Marys -0.3% -0.1% 36 56%
Arizona -0.3% 0.2% 37 54%
Akron -0.3% -0.2% 38 61%
GWU -0.3% -0.1% 34 59%
Washington St. -0.3% -0.2% 23 52%
TCU -0.3% -0.2% 45 58%
Delaware -0.2% -0.3% 40 58%
Kansas -0.2% -0.3% 40 65%
Illinois -0.2% 0.1% 33 61%
Texas A&M -0.2% -0.3% 35 63%
Niagara -0.2% -0.4% 24 54%
Davidson -0.2% -0.2% 37 54%
UC Davis -0.2% -0.1% 35 57%
William & Mary -0.2% 0.1% 30 53%
North Florida -0.2% -0.1% 24 50%
Brigham Young -0.2% 0.2% 27 56%
Missouri -0.2% 0.0% 35 51%
Loyola MD -0.2% -0.3% 27 59%
Georgia Tech -0.2% 0.1% 37 54%
Eastern Ill -0.1% 0.4% 29 52%
California -0.1% -0.1% 49 59%
New Mexico St -0.1% 0.1% 42 60%
Youngstown St -0.1% 0.1% 23 57%
West Virginia -0.1% 0.1% 31 52%
SMU -0.1% -0.2% 35 54%
Miami FL -0.1% 0.3% 28 54%
Boston U -0.1% -0.3% 28 54%
Fordham -0.1% 0.1% 40 53%
Vermont -0.1% 0.4% 40 53%
Nevada -0.1% 0.4% 26 54%
Utah -0.1% -0.2% 49 53%
Bryant U 0.0% -0.2% 41 51%
St. Louis 0.0% -0.1% 26 58%
SIUC 0.0% 0.0% 50 52%
George Mason 0.0% -0.3% 27 52%
Ball State 0.0% -0.3% 33 52%
Kentucky 0.0% 0.1% 37 51%
Xavier 0.0% 0.0% 55 49%
Virginia 0.0% -0.1% 40 50%
San Diego 0.0% 0.6% 35 49%
Evansville 0.0% 0.2% 61 48%
St. Francis Pa. 0.0% 0.2% 54 50%
Connecticut 0.0% -0.3% 39 49%
Idaho 0.0% 0.2% 40 43%
Yale 0.1% 0.0% 23 48%
Dartmouth 0.1% 0.0% 28 46%
Iowa 0.1% 0.5% 31 48%
UCLA 0.1% 0.2% 38 47%
Wis.- Green Bay 0.1% -0.1% 24 50%
Army 0.1% 0.0% 32 47%
Northeastern 0.1% -0.1% 37 49%
Lehigh 0.1% 0.0% 27 44%
Arizona St 0.1% -0.2% 36 44%
Wyoming 0.1% 0.4% 33 36%
Air Force 0.1% 0.1% 32 47%
La Salle 0.1% 0.2% 22 32%
Rider 0.1% 0.6% 29 48%
CSUB 0.1% 0.3% 45 49%
Maine 0.1% 0.0% 60 45%
Notre Dame 0.2% 0.2% 36 44%
Vanderbilt 0.2% 0.3% 35 46%
Drexel 0.2% 0.6% 39 41%
Butler 0.2% 0.8% 55 45%
UCSB 0.2% 0.5% 56 36%
Villanova 0.2% 0.1% 36 47%
Rhode Island 0.2% 0.2% 38 37%
Oregon St 0.2% 0.1% 28 46%
UNC Wilmington 0.2% 0.3% 38 39%
Missouri St 0.2% 0.7% 33 45%
Rutgers 0.2% 0.3% 29 45%
Stanford 0.2% 0.1% 41 46%
Cal Poly 0.2% 0.3% 49 37%
Georgia 0.2% 0.0% 30 43%
Harvard 0.2% 0.4% 26 38%
IUPUI 0.3% -0.2% 41 49%
UNC 0.3% 0.7% 29 41%
Penn 0.3% 0.5% 23 39%
UMBC 0.3% 0.4% 50 42%
Brown 0.3% 0.3% 25 36%
Duquesne 0.3% 0.0% 43 42%
Michigan St 0.3% 0.3% 32 34%
Marist 0.3% 0.4% 23 43%
Indiana State 0.3% 0.8% 45 44%
Cincinnati 0.3% 0.3% 38 42%
Colgate 0.3% 0.6% 34 44%
LIU Brooklyn 0.3% 0.2% 24 46%
Alabama 0.3% 0.8% 29 38%
UNC Asheville 0.4% 0.7% 44 36%
Georgetown 0.4% 0.6% 35 40%
Pacific 0.4% 0.3% 38 39%
Columbia 0.4% 0.3% 24 38%
Northwestern 0.4% 0.3% 33 48%
Northern Iowa 0.4% 0.3% 46 39%
Canisius 0.4% 0.5% 27 37%
Campbell 0.4% 0.5% 39 38%
Denver 0.4% 0.6% 43 35%
Pittsburgh 0.5% 0.9% 36 31%
Bucknell 0.5% 0.1% 33 33%
Illinois St 0.5% 0.8% 44 36%
Wisconsin 0.5% 0.5% 42 38%
UNLV 0.5% 0.2% 23 43%
East Carolina 0.5% 0.3% 19 37%
Loy. Marymount 0.5% 0.6% 52 40%
Colorado St. 0.5% 0.4% 32 38%
Cleveland St 0.5% 0.7% 40 33%
Michigan 0.6% 0.4% 50 32%
St. Bonaventure 0.6% 0.6% 11 45%
Southern Cali 0.6% 0.6% 53 40%
Princeton 0.6% 0.6% 28 29%
Oakland 0.6% 0.3% 35 31%
Purdue 0.6% 0.5% 41 37%
Saint Peters 0.6% 1.3% 7 29%
Seattle U 0.6% 1.1% 38 29%
Minnesota 0.6% 0.7% 44 34%
South Dakota St 0.6% 1.2% 41 34%
Valparaiso 0.7% 0.9% 18 33%
Ark.-Little Rock 0.7% 0.9% 48 29%
New Mexico 0.7% 0.8% 25 28%
Massachusetts 0.7% 0.4% 46 41%
Louisville 0.7% 0.6% 42 33%
Texas 0.8% 0.8% 59 24%
Binghamton 0.8% 0.9% 46 37%
Nebraska 0.8% 0.9% 48 27%
Sacred Heart 0.8% 0.9% 46 26%
Wis.- Milwaukee 0.9% 0.8% 25 32%
Virginia Tech 0.9% 0.9% 22 27%
Manhattan 1.0% 1.6% 21 19%
Florida Gulf 1.0% 1.2% 48 25%
Liberty 1.0% 1.4% 43 19%
Iona Coll 1.0% 0.6% 43 35%
St. Francis 1.2% 1.5% 23 17%
Western Ill 1.2% 1.2% 20 25%
Wagner 1.2% 1.8% 48 17%
Illinois-Chicago 1.2% 1.4% 31 19%
Howard 1.3% 1.1% 17 29%
South Dakota 1.5% 1.2% 27 11%
Seton Hall 1.5% 1.8% 45 20%
GA Southern 1.6% 1.8% 51 18%
Gardner-Webb 2.1% 2.3% 41 20%

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curious
5 years ago

How about for DII?

marley09
5 years ago

Ignoring the Stanford-not-resting controversy, the line that jumped out and hit me over the head was the median/average time improvement year to year excluding freshmen is -.1%/-.2% (ignoring standard deviation). Is this accurate, normal and expected? I’m not questioning Mering’s methodology or data I’m just having trouble wrapping my head around the fact that these swimmers aren’t getting faster after their freshmen year.

hswimmer
5 years ago

Getting ready for my picks this year! Going to choose a lot smarter and not go off of your previews!

The michael phelps caterpillar
5 years ago

Every team I have ever coached produced best times across the board. My secret? If you don’t get a best time I verbally accost you until you quit.

hswimmer
Reply to  The michael phelps caterpillar
5 years ago

TROLLL

2 Cents
5 years ago

Haha, y’all just cant sit back there at SwimSwam HQ and take a day off huh? These articles and stat reviews are interesting though… Keep it up, and enjoy your time off in a few weeks right after Men’s NCAA’s…. and yes y’all need to take some well earned time off.

RIDIC!
5 years ago

This was a great article until I came across a line of b.s. I just couldn’t stomach even if it came straight from Meehan’s mouth. Stanford didn’t rest at all for its conference meet? Is this line of the article located in an alternative universe for what rest/tapor means? One could say they weren’t fully rested/tapered but most top programs, if they can, leave another level or layer (even if its psychological) for the final end season push. Stanford swam quite well at pac 12s; really fast as other articles have noted. They’re not superhuman (except for Ledecky and she’s graduated) where they don’t rest at all and other teams rest fully and then they dominate. No doubt, as a… Read more »

2 Cents
Reply to  RIDIC!
5 years ago

The NC State men will try to claim the same thing… could they both be right? maybe… but just the nature of a conference meet will involve some rest… so I agree with you. Do not say they had zero or no rest.

Taa
Reply to  RIDIC!
5 years ago

You can tell who rested and who didn’t. Tankersly and Pitzer obviously rested. Forde and Drabot not so much. Eastin and Howe previously both set AR at conference and then added time at NCAAs so how do they claim they werent rested for conference. Hansson from USC flat out stated she didnt rest at all for conference after her AR. Go figure.

Ryan
5 years ago

Was C-USA not included?