Recently we looked at points change vs the psych sheet at nationals. However, this doesn’t tell the full story of who swam well and who didn’t. A swimmer seeded in the top 8 who adds 2% to their seed time is captured in the points change metric, but a swimmer seeded 20th who adds 2% isn’t. Both should be included in a measure of a team’s performance, so I’ve compiled team’s average percentage time change from their seed times at the meet (this data for the previous 7 years).
As expected from the points change data, the best performing teams were Kentucky, Missouri, and Texas A&M. Kentucky led schools with a reasonable sample size by dropping an average of .23% from 23 swims. Missouri and Texas A&M each dropped an average of .09% from their seed times. None of the other top schools dropped time on average. Stanford added .31%, California added .3%, Georgia added .2%, and Texas added .16%. The worst performing big teams were both from Los Angeles. USC added an average of 1.33% and UCLA added 1.23%. The field as a whole added time in line with the historical average. The average time change over the last 7 years at this meet was an add of .45%. This year swimmers added an average of .43%.
Kaitlyn Jones of Virginia had the biggest time drop of the entire meet. She dropped 4.88% in her 100 back, going 53.16 from a seed time of 55.89. Next best was Erin Falconer of Auburn who dropped 3.64% in her 100 back (53.97 to 56.01), then Nadine Laemmler of Missouri who dropped 2.73% in the 100 back (51.96 to 50.54), and Amy Bilquist of California who dropped 2.54% in the 100 free (48.97 to 47.55). The biggest time add of the meet was Christina Elmgreen of Florida Gulf Coast who added 4.19% in the 200 IM (1:59.65 to 2:04.66). Longer lists of top adds and drops can be found at the bottom of this article below the tables for whole team average time changes and top/bottom performance for each team.
Team Time Change Averages
Negative is faster, positive is slower. This matches the “dropped time,” “added time” style of talking about performance
| Average Time Change At Nationals | Number of Times | Standard Deviation | |
| UMBC | -0.72% | 3 | 0.24% |
| Davidson | -0.39% | 3 | 0.55% |
| Kentucky | -0.23% | 23 | 0.90% |
| Iowa | -0.18% | 3 | 0.66% |
| Missouri | -0.09% | 23 | 1.02% |
| Texas A&M | -0.09% | 37 | 0.93% |
| Auburn | 0.03% | 24 | 1.29% |
| Louisville | 0.04% | 19 | 0.83% |
| Denver | 0.08% | 12 | 1.13% |
| Michigan | 0.10% | 26 | 0.97% |
| Purdue | 0.12% | 6 | 0.64% |
| Arizona | 0.13% | 23 | 0.90% |
| Drexel | 0.14% | 2 | 1.54% |
| Texas | 0.16% | 26 | 0.85% |
| Georgia | 0.20% | 37 | 1.07% |
| Cincinnati | 0.24% | 3 | 0.47% |
| Indiana | 0.29% | 16 | 1.36% |
| California | 0.30% | 38 | 1.26% |
| Minnesota | 0.30% | 15 | 1.43% |
| UC Davis | 0.31% | 3 | 0.18% |
| Stanford | 0.31% | 39 | 0.93% |
| Penn St | 0.32% | 8 | 1.27% |
| LSU | 0.32% | 6 | 0.52% |
| NC State | 0.34% | 26 | 0.73% |
| Central Conn St | 0.35% | 2 | 0.73% |
| Virginia | 0.39% | 25 | 1.62% |
| Florida St | 0.40% | 8 | 0.95% |
| Harvard | 0.43% | 3 | 0.59% |
| Notre Dame | 0.48% | 11 | 0.63% |
| UNC | 0.50% | 14 | 0.89% |
| Florida | 0.50% | 21 | 1.02% |
| South Carolina | 0.50% | 5 | 1.48% |
| Akron | 0.52% | 7 | 0.60% |
| Virginia Tech | 0.54% | 12 | 0.76% |
| Tennessee | 0.57% | 20 | 1.00% |
| Air Force | 0.59% | 3 | 0.43% |
| Liberty | 0.61% | 2 | 0.62% |
| Arkansas | 0.63% | 9 | 0.82% |
| Eastern Mich | 0.63% | 4 | 0.74% |
| Seattle U | 0.68% | 3 | 0.32% |
| Rutgers | 0.70% | 4 | 0.79% |
| Arizona St | 0.78% | 9 | 0.71% |
| Wisconsin | 0.82% | 19 | 1.14% |
| East Carolina | 0.82% | 2 | 0.73% |
| Buffalo | 0.83% | 3 | 0.53% |
| Northwestern | 0.84% | 5 | 1.03% |
| Ohio St | 0.85% | 21 | 1.08% |
| Boise St | 0.88% | 8 | 1.10% |
| Duke | 1.03% | 7 | 0.85% |
| Pittsburgh | 1.04% | 8 | 1.53% |
| Hawaii | 1.05% | 6 | 0.78% |
| Miami (FL) | 1.15% | 3 | 0.85% |
| Alabama | 1.22% | 5 | 0.57% |
| UCLA | 1.23% | 18 | 1.30% |
| Marshall | 1.32% | 3 | 0.24% |
| Southern Cali | 1.33% | 36 | 1.25% |
| Florida Intl | 1.37% | 3 | 0.26% |
| SMU | 1.48% | 3 | 0.72% |
| Rice | 1.63% | 2 | 0.28% |
| Utah | 1.66% | 4 | 0.92% |
| Wyoming | 1.88% | 2 | 0.24% |
| Florida Gulf | 2.01% | 4 | 1.88% |
Biggest Drop and Add for Each Team
| Biggest Drop At Nationals | Biggest Time Add At Nationals | |||||||||
| Name | Event | Time Change | Seed Time | Nationals Time | Name | Event | Time Change | Seed Time | Nationals Time | |
| Air Force | Miller, Genevieve | 500 Freestyle | 0.30% | 4:38.98 | 4:39.82 | Miller, Genevieve | 200 Freestyle | 1.09% | 1:47.19 | 1:48.36 |
| Akron | Myers, Madison | 100 Freestyle | -0.49% | 49.33 | 49.09 | Szynal, Luka | 200 Backstroke | 1.27% | 1:52.94 | 1:54.37 |
| Alabama | Scott, Bailey | 50 Freestyle | 0.50% | 21.84 | 21.95 | Nonnenberg, Mia | 500 Freestyle | 2.08% | 4:43.20 | 4:49.08 |
| Arizona | Lohman, Kennedy | 200 Breastroke | -1.43% | 2:14.21 | 2:12.29 | Rumrill, Mackenzie | 200 IM | 2.44% | 1:59.39 | 2:02.30 |
| Arizona St | Fisch, Claire | 100 Freestyle | -0.63% | 49.2 | 48.89 | Simonovic, Kat | 500 Freestyle | 1.49% | 4:40.53 | 4:44.70 |
| Arkansas | Macias, Ayumi | 500 Freestyle | -0.52% | 4:42.39 | 4:40.92 | Tatlow, Chelsea | 200 IM | 1.97% | 1:59.50 | 2:01.86 |
| Auburn | Falconer, Erin | 100 Backstroke | -3.64% | 56.01 | 53.97 | Falconer, Erin | 200 Backstroke | 2.75% | 1:54.40 | 1:57.55 |
| Boise St | Martin, Katelyn | 100 Freestyle | -0.16% | 48.98 | 48.9 | Chard, Emma | 1650 Freestyle | 2.86% | 16:17.11 | 16:45.05 |
| Buffalo | Burns, Megan | 100 Freestyle | 0.44% | 48.14 | 48.35 | Burns, Megan | 200 Freestyle | 1.43% | 1:46.07 | 1:47.59 |
| California | Bilquist, Amy | 100 Freestyle | -2.54% | 48.79 | 47.55 | Li, Celina | 400 IM | 3.34% | 4:06.76 | 4:15.00 |
| Central Conn St | Garber, Maddy | 200 Breastroke | -0.17% | 2:13.35 | 2:13.12 | Garber, Maddy | 100 Breastroke | 0.87% | 1:00.01 | 1:00.53 |
| Cincinnati | Keire, Jackie | 50 Freestyle | -0.14% | 22.19 | 22.16 | Keire, Jackie | 100 Freestyle | 0.77% | 47.95 | 48.32 |
| Davidson | Lankiewicz, Elise | 100 Freestyle | -1.00% | 49.11 | 48.62 | Lankiewicz, Elise | 200 Freestyle | 0.09% | 1:45.14 | 1:45.23 |
| Denver | Andison, Bailey | 400 IM | -1.74% | 4:07.40 | 4:03.09 | Myers, Maddie | 400 IM | 2.68% | 4:09.54 | 4:16.24 |
| Drexel | Bernhardt, Rachel | 100 Breastroke | -0.95% | 1:00.25 | 59.68 | Bernhardt, Rachel | 200 Breastroke | 1.22% | 2:10.62 | 2:12.22 |
| Duke | Rusch, Maddie | 100 Freestyle | -0.28% | 49.32 | 49.18 | Goldman, Leah | 200 IM | 2.05% | 1:57.33 | 1:59.74 |
| East Carolina | Norrman, Vendela | 100 Breastroke | 0.31% | 1:01.58 | 1:01.77 | Norrman, Vendela | 200 Breastroke | 1.34% | 2:10.28 | 2:12.02 |
| Eastern Mich | Mitcheltree, Alexis | 200 Backstroke | -0.11% | 1:56.74 | 1:56.61 | Mitcheltree, Alexis | 100 Backstroke | 1.37% | 52.57 | 53.29 |
| Florida | Burns, Hannah | 200 IM | -1.59% | 2:00.23 | 1:58.32 | Yambor-Maul, Alyssa | 200 Butterfly | 2.01% | 1:55.68 | 1:58.01 |
| Florida Gulf | Latham, Katie | 50 Freestyle | -0.36% | 22.34 | 22.26 | Elmgreen, Christina Kaas | 200 IM | 4.19% | 1:59.65 | 2:04.66 |
| Florida Intl | Bertelli, Letizia | 100 Freestyle | 1.16% | 48.32 | 48.88 | Ruele, Naomi | 100 Backstroke | 1.66% | 52.87 | 53.75 |
| Florida St | Lovemore, Tayla | 100 Butterfly | -0.81% | 52.02 | 51.6 | Lovemore, Tayla | 50 Freestyle | 1.81% | 22.1 | 22.5 |
| Georgia | Stewart, Kylie | 200 Backstroke | -2.01% | 1:54.00 | 1:51.71 | McCann, Meryn | 500 Freestyle | 2.44% | 4:38.62 | 4:45.41 |
| Harvard | Dahlke, Miki | 100 Freestyle | -0.25% | 48.9 | 48.78 | Dahlke, Miki | 50 Freestyle | 0.83% | 22.8 | 22.99 |
| Hawaii | Hansen, Bryndis | 200 Freestyle | 0.09% | 1:46.93 | 1:47.03 | Hansen, Bryndis | 100 Freestyle | 1.83% | 48.55 | 49.44 |
| Indiana | Goss, Kennedy | 500 Freestyle | -1.96% | 4:41.64 | 4:36.13 | Pressey, Bailey | 400 IM | 3.92% | 4:10.16 | 4:19.96 |
| Iowa | Sougstad, Emma | 100 Breastroke | -0.88% | 59.31 | 58.79 | Sougstad, Emma | 200 IM | 0.44% | 1:57.98 | 1:58.50 |
| Kentucky | Freriks, Geena | 100 Freestyle | -1.34% | 49.32 | 48.66 | Casey, Kendal | 500 Freestyle | 1.73% | 4:40.81 | 4:45.66 |
| Liberty | Finnigan, Alicia | 100 Butterfly | 0.17% | 53.74 | 53.83 | Finnigan, Alicia | 200 Butterfly | 1.05% | 1:56.15 | 1:57.37 |
| Louisville | Comerford, Mallory | 200 Freestyle | -1.32% | 1:41.70 | 1:40.36 | Houck, Abbie | 500 Freestyle | 1.44% | 4:42.41 | 4:46.47 |
| LSU | Troskot, Leah | 100 Freestyle | -0.60% | 48.53 | 48.24 | Kopcso, Kara | 200 Butterfly | 0.92% | 1:55.66 | 1:56.72 |
| Marshall | Rowe, Sirena | 100 Freestyle | 1.15% | 49.53 | 50.1 | Rowe, Sirena | 50 Freestyle | 1.59% | 22.08 | 22.43 |
| Miami (FL) | Algee, Angela | 200 Butterfly | 0.44% | 1:58.38 | 1:58.90 | Algee, Angela | 100 Butterfly | 2.10% | 52.01 | 53.1 |
| Michigan | Deloof, Gabby | 50 Freestyle | -2.35% | 23.01 | 22.47 | McCann, Carolyn | 100 Breastroke | 1.84% | 1:00.33 | 1:01.44 |
| Minnesota | Horejsi, Lindsey | 100 Breastroke | -1.48% | 58.9 | 58.03 | Zeiger, Brooke | 400 IM | 3.82% | 4:02.71 | 4:11.99 |
| Missouri | Laemmler, Nadine | 100 Backstroke | -2.73% | 51.96 | 50.54 | Suek, Ellie | 400 IM | 1.61% | 4:10.33 | 4:14.37 |
| NC State | Brumbaum, Kayla | 200 Breastroke | -1.55% | 2:07.53 | 2:05.55 | Labonge, Natalie | 50 Freestyle | 1.73% | 22 | 22.38 |
| Northwestern | Gruest Slowing, Valerie | 1650 Freestyle | -0.65% | 16:01.28 | 15:55.01 | Postoll, Melissa | 400 IM | 1.85% | 4:08.76 | 4:13.37 |
| Notre Dame | Mulquin, Catherine | 100 Backstroke | -0.79% | 52.13 | 51.72 | Smith, Katie | 50 Freestyle | 1.57% | 22.25 | 22.6 |
| Ohio St | Li, Zhesi | 50 Freestyle | -0.88% | 21.48 | 21.29 | Vargo, Taylor | 100 Breastroke | 3.46% | 59.86 | 1:01.93 |
| Penn St | McHugh, Ally | 1650 Freestyle | -0.91% | 16:07.69 | 15:58.92 | Sowinski, Katelyn | 200 Butterfly | 3.19% | 1:55.97 | 1:59.67 |
| Pittsburgh | Rathsack, Lina | 100 Breastroke | -1.34% | 59.8 | 59 | Rathsack, Lina | 200 IM | 2.94% | 1:57.66 | 2:01.12 |
| Purdue | Meitz, Kaersten | 1650 Freestyle | -0.71% | 16:10.41 | 16:03.48 | Meitz, Kaersten | 200 Freestyle | 0.99% | 1:44.78 | 1:45.82 |
| Rice | Schillinger, Marie-Claire | 200 Breastroke | 1.44% | 2:10.92 | 2:12.80 | Schillinger, Marie-Claire | 100 Breastroke | 1.83% | 1:00.13 | 1:01.23 |
| Rutgers | Koprivova, Vera | 200 Backstroke | -0.18% | 1:53.94 | 1:53.74 | Stoppa, Francesca | 200 Butterfly | 1.37% | 1:56.20 | 1:57.79 |
| Seattle U | Wittenauer-Lee, Blaise | 100 Breastroke | 0.31% | 1:00.52 | 1:00.71 | Wittenauer-Lee, Blaise | 200 IM | 0.88% | 1:59.95 | 2:01.00 |
| SMU | Samardzic, Matea | 200 Backstroke | 0.65% | 1:52.69 | 1:53.42 | Erasmus, Marne | 100 Butterfly | 1.93% | 51.42 | 52.41 |
| South Carolina | Barksdale, Emma | 200 Breastroke | -0.36% | 2:11.30 | 2:10.83 | Dirrane, Kersten | 200 Breastroke | 3.11% | 2:08.58 | 2:12.58 |
| Southern Cali | Mann, Becca | 500 Freestyle | -1.30% | 4:42.44 | 4:38.77 | Vose, Kirsten | 200 IM | 3.87% | 1:55.91 | 2:00.39 |
| Stanford | Manuel, Simone | 100 Freestyle | -1.73% | 46.36 | 45.56 | Drabot, Katie | 500 Freestyle | 2.13% | 4:35.69 | 4:41.56 |
| Tennessee | Brown, Erika | 100 Freestyle | -1.76% | 49.33 | 48.46 | Cefal, Michelle | 200 Butterfly | 2.19% | 1:56.18 | 1:58.72 |
| Texas | Cox, Madisyn | 200 Breastroke | -1.13% | 2:07.21 | 2:05.77 | Evans, Joanna | 500 Freestyle | 1.95% | 4:36.97 | 4:42.37 |
| Texas A&M | Rasmus, Claire | 100 Freestyle | -1.44% | 49.35 | 48.64 | Gonzalez-Hermosillo, Monika | 200 Breastroke | 1.97% | 2:11.50 | 2:14.09 |
| UC Davis | Laughlin, Solie | 200 Backstroke | 0.10% | 1:54.48 | 1:54.60 | Laughlin, Solie | 200 IM | 0.43% | 1:59.74 | 2:00.25 |
| UCLA | Grover, Katie | 100 Freestyle | -0.91% | 49.28 | 48.83 | Mack, Linnea | 50 Freestyle | 3.41% | 21.67 | 22.41 |
| UMBC | Escobedo, Emily | 100 Breastroke | -0.91% | 59.02 | 58.48 | Escobedo, Emily | 200 IM | -0.46% | 1:55.66 | 1:55.13 |
| UNC | Moffitt, Hellen | 100 Butterfly | -0.96% | 50.86 | 50.37 | Baldwin, Caroline | 100 Backstroke | 1.50% | 51.38 | 52.15 |
| Utah | Colleou, Stina | 100 Breastroke | 0.88% | 1:01.29 | 1:01.83 | Colleou, Stina | 200 Breastroke | 2.89% | 2:09.90 | 2:13.66 |
| Virginia | Jones, Kaitlyn | 100 Backstroke | -4.88% | 55.89 | 53.16 | Tafuto, Vivian | 200 IM | 4.12% | 1:58.80 | 2:03.70 |
| Virginia Tech | Nazieblo, Klaudia | 400 IM | -1.22% | 4:15.77 | 4:12.65 | Hicks, Chloe | 200 Backstroke | 1.63% | 1:53.70 | 1:55.55 |
| Wisconsin | Unicomb, Jess | 50 Freestyle | -0.79% | 22.79 | 22.61 | Grindall, Dana | 100 Butterfly | 2.46% | 52.08 | 53.36 |
| Wyoming | Harutjunjan, Maria | 200 Breastroke | 1.71% | 2:11.53 | 2:13.78 | Harutjunjan, Maria | 100 Breastroke | 2.06% | 59.85 | 1:01.08 |
Biggest Time Drops from Seed
| Team | Time Change | Event | Seed Time | Nationals Time | ||
| 1 | Jones, Kaitlyn | Virginia | -4.88% | 100 Backstroke | 55.89 | 53.16 |
| 2 | Falconer, Erin | Auburn | -3.64% | 100 Backstroke | 56.01 | 53.97 |
| 3 | Laemmler, Nadine | Missouri | -2.73% | 100 Backstroke | 51.96 | 50.54 |
| 4 | Bilquist, Amy | California | -2.54% | 100 Freestyle | 48.79 | 47.55 |
| 5 | Deloof, Gabby | Michigan | -2.35% | 50 Freestyle | 23.01 | 22.47 |
| 6 | Stewart, Kylie | Georgia | -2.01% | 200 Backstroke | 1:54.00 | 1:51.71 |
| 7 | Goss, Kennedy | Indiana | -1.96% | 500 Freestyle | 4:41.64 | 4:36.13 |
| 8 | Brown, Erika | Tennessee | -1.76% | 100 Freestyle | 49.33 | 48.46 |
| 9 | Andison, Bailey | Denver | -1.74% | 400 IM | 4:07.40 | 4:03.09 |
| 10 | Manuel, Simone | Stanford | -1.73% | 100 Freestyle | 46.36 | 45.56 |
| 11 | Laemmler, Nadine | Missouri | -1.65% | 200 Backstroke | 1:52.65 | 1:50.79 |
| 12 | Stewart, Kylie | Georgia | -1.63% | 100 Backstroke | 52.65 | 51.79 |
| 13 | Burns, Hannah | Florida | -1.59% | 200 IM | 2:00.23 | 1:58.32 |
| 14 | Brumbaum, Kayla | NC State | -1.55% | 200 Breastroke | 2:07.53 | 2:05.55 |
Biggest Time Adds to Seed
| Name | Team | Time Change | Event | Seed Time | Nationals Time | |
| 1 | Elmgreen, Christina Kaas | Florida Gulf | 4.19% | 200 IM | 1:59.65 | 2:04.66 |
| 2 | Tafuto, Vivian | Virginia | 4.12% | 200 IM | 1:58.80 | 2:03.70 |
| 3 | Pressey, Bailey | Indiana | 3.92% | 400 IM | 4:10.16 | 4:19.96 |
| 4 | Vose, Kirsten | Southern Cali | 3.87% | 200 IM | 1:55.91 | 2:00.39 |
| 5 | Zeiger, Brooke | Minnesota | 3.82% | 400 IM | 4:02.71 | 4:11.99 |
| 6 | Weiss, Hannah | Southern Cali | 3.50% | 100 Backstroke | 52.56 | 54.4 |
| 7 | Moseley, Stanzi | Southern Cali | 3.49% | 200 Freestyle | 1:43.98 | 1:47.61 |
| 8 | Vargo, Taylor | Ohio St | 3.46% | 100 Breastroke | 59.86 | 1:01.93 |
| 9 | Mack, Linnea | UCLA | 3.41% | 50 Freestyle | 21.67 | 22.41 |
| 10 | Li, Celina | California | 3.34% | 400 IM | 4:06.76 | 4:15.00 |
| 11 | Leach, Hanni | Southern Cali | 3.32% | 200 Backstroke | 1:52.58 | 1:56.32 |
| 12 | Weiss, Hannah | Southern Cali | 3.32% | 200 Backstroke | 1:55.00 | 1:58.82 |
| 13 | Vargo, Taylor | Ohio St | 3.32% | 200 Breastroke | 2:08.56 | 2:12.83 |
| 14 | Sowinski, Katelyn | Penn St | 3.19% | 200 Butterfly | 1:55.97 | 1:59.67 |
| 15 | Vose, Kirsten | Southern Cali | 3.13% | 200 Breastroke | 2:07.65 | 2:11.65 |
| 16 | Dirrane, Kersten | South Carolina | 3.11% | 200 Breastroke | 2:08.58 | 2:12.58 |
| 17 | Mack, Linnea | UCLA | 3.11% | 100 Backstroke | 50.56 | 52.13 |
Sorry–team point improvement is a more accurate gauge of championship season success. Individual time drops are relative to a swimmer’s development (experience, which meet is targeted, etc.). Point total improvement reflects coaching strategy–how they prepared their potential point scorers for team success at the national level, and how the swimmers executed on the plan.
In this metric, a team can actually appear less successful for getting a bunch of swimmers qualified at the conference meet (if non-qualifiers cut a ton of time at their conference meet, then swim slower at NCAAs, they appear less successful). Because context isn’t considered, it turns what is logically seen as a positive into a negative. For individuals it might have some value, but… Read more »
Most accurate objective gauge of championship season success = actual points scored (ie, team placing / event placing). Everything else is just a personal goal (which is perfectly legitimate, but measurable by you alone) or mind games (which is a complete waste of everyone’s time).
again, still don’t see the purpose in making a chart of ‘biggest time adds’.
Thanks for sharing the seven year history and sd’s – useful for adjusting psych sheet forecasts in the future. Using raw diving scores from the various zone qualifying meets turned out to be a useful technique to adjust for diving points as well. Using this method, Minnesota was forecasted to benefit most from diving with 65 points, and they actually scored 95 – by far the biggest over performer as well. UCLA was forecasted at 49 and scored 43; Indiana 40/27, S Carolina 36/4, Nev 30/25, Tex 28/20, Miami OH 25/29, LSU 21/14, Purdue 19/29, Stanford 18/27, Mizzou 18/18, ASU 17/9, Neb 16/15, Northwestern 15/31, Haw 13/0, OSU 12/0, UK 11/4, Air Force 9/0, TAM 7/0, UTAH 6/0, Mich 3/12,… Read more »
This is interesting, but because of total subjectivity in the sport, I’m not sure it is quite as applicable. It might be more predictive to average dive lists for participating athletes from their final dual meet, conference and Zone dive lists (approximately 5 in total), then place them. Greater high level sample size is definitely more predictive of result.
To be clear, was not trying to gauge a “performance vs seed” analysis for diving. The forecasted team scores based on psych sheet which were presented excluded any assumptions for diving (a significant limitation if you are really interested in final team placing). What I just shared was simply a test to see if you could improve the accuracy of the forecast if you layered on expected scores for diving based on zone diving scores. It appears to me that this in fact yielded useful results — there may be (probably are) better methods, but I haven’t seen any put forward to this point.
Great data. Excellent work.