The pick ’em contest can give some insight into what swimswam readers in general think or hope will happen at the Olympics. Swimswam reader’s main consensus is that the US will win lots of medals. The medal table implied by the aggregated picks has the US winning 32.9 medals total and 13.2 golds (ex. if 50% of entries pick the US to win gold in an event, the US is given .5 of a gold medal in the total). This would be more than the 31 medals the US won in London.
Pick’s medal table:
| Gold | Silver | Bronze | Total | |
| USA | 13.2 | 10.7 | 9.0 | 32.9 |
| AUS | 7.3 | 6.5 | 4.3 | 18.1 |
| JPN | 2.0 | 2.1 | 2.2 | 6.3 |
| GBR | 1.2 | 1.7 | 2.5 | 5.4 |
| HUN | 2.3 | 1.7 | 1.3 | 5.4 |
| CHN | 1.5 | 1.4 | 1.3 | 4.3 |
| SWE | 1.1 | 1.4 | 1.5 | 4.0 |
| ITA | 0.7 | 0.8 | 1.2 | 2.8 |
| RSA | 0.2 | 1.4 | 1.2 | 2.7 |
| FRA | 1.1 | 0.7 | 0.9 | 2.7 |
| NED | 0.1 | 0.7 | 1.4 | 2.1 |
| GER | 0.3 | 0.5 | 0.5 | 1.3 |
| DEN | 0.1 | 0.5 | 0.6 | 1.1 |
| LTU | 0.4 | 0.4 | 0.3 | 1.0 |
| CAN | 0.0 | 0.1 | 0.9 | 1.0 |
| TUR | 0.2 | 0.4 | 0.2 | 0.8 |
| NZL | 0.0 | 0.4 | 0.3 | 0.7 |
| ESP | 0.2 | 0.2 | 0.3 | 0.8 |
| BRA | 0.0 | 0.2 | 0.6 | 0.8 |
| SIN | 0.0 | 0.1 | 0.4 | 0.6 |
| RUS | 0.0 | 0.1 | 0.4 | 0.6 |
| JAM | 0.0 | 0.0 | 0.3 | 0.3 |
| POL | 0.0 | 0.0 | 0.2 | 0.2 |
| KOR | 0.0 | 0.0 | 0.1 | 0.1 |
Picks Men Only Medal Table:
| Men | Gold | Silver | Bronze | Total |
| USA | 7.8 | 5.1 | 5.2 | 18.1 |
| AUS | 2.1 | 3.5 | 2.0 | 7.7 |
| JPN | 1.0 | 1.4 | 1.5 | 3.9 |
| GBR | 1.2 | 1.2 | 1.3 | 3.7 |
| RSA | 0.2 | 1.4 | 1.2 | 2.7 |
| CHN | 1.3 | 0.7 | 0.5 | 2.5 |
| FRA | 1.1 | 0.7 | 0.9 | 2.6 |
| HUN | 0.3 | 0.9 | 0.6 | 1.8 |
| ITA | 0.7 | 0.3 | 0.3 | 1.4 |
| GER | 0.2 | 0.3 | 0.4 | 0.9 |
| BRA | 0.0 | 0.1 | 0.6 | 0.7 |
| SIN | 0.0 | 0.1 | 0.4 | 0.6 |
| RUS | 0.0 | 0.1 | 0.4 | 0.5 |
| CAN | 0.0 | 0.0 | 0.3 | 0.3 |
| POL | 0.0 | 0.0 | 0.2 | 0.2 |
| KOR | 0.0 | 0.0 | 0.1 | 0.1 |
| LTU | 0.0 | 0.0 | 0.1 | 0.1 |
Picks Women Only Medal Table:
| Gold | Silver | Bronze | Total | |
| USA | 5.4 | 5.6 | 3.8 | 14.8 |
| AUS | 5.2 | 2.9 | 2.3 | 10.4 |
| SWE | 1.1 | 1.4 | 1.5 | 4.0 |
| HUN | 2.0 | 0.8 | 0.7 | 3.6 |
| JPN | 1.0 | 0.7 | 0.7 | 2.4 |
| NED | 0.1 | 0.7 | 1.4 | 2.1 |
| GBR | 0.0 | 0.5 | 1.2 | 1.7 |
| CHN | 0.2 | 0.7 | 0.8 | 1.8 |
| ITA | 0.0 | 0.5 | 0.8 | 1.4 |
| DEN | 0.1 | 0.5 | 0.6 | 1.1 |
| LTU | 0.4 | 0.4 | 0.2 | 1.0 |
| TUR | 0.2 | 0.4 | 0.2 | 0.8 |
| NZL | 0.0 | 0.4 | 0.3 | 0.7 |
| ESP | 0.2 | 0.2 | 0.3 | 0.8 |
| CAN | 0.0 | 0.1 | 0.6 | 0.7 |
| GER | 0.0 | 0.1 | 0.2 | 0.4 |
| JAM | 0.0 | 0.0 | 0.3 | 0.3 |
-99% of entries have Katie Ledecky winning the 400 and 800 free. JamieTW, TheShiftyShadow,Jay Dubleyew, and ORRDU1 picked here to lose the 400. mfnisratty picked her to lose the 800. Jay Dubleyew, and Iva picked her to lose both. I wish them luck.
-Other big favorites were Katink Hozzzu, Women’s 200 IM, 95%; Emily Seebohm, Women’s 100 back 94%; Cate Campbell, Women’s 100 free, 92%; Adam Peaty, Men’s 100 breast, 91%.
-The only individual event where no one was picked to win gold by more than 50% of entries was the women’s 200 fly. The favorites there were Madeline Groves 38%, Natsumi Hoshi, 29%, Mireia Belmonte 21%, Cammile Adams 6%, Franziska Hentke 5%, and Yufei Zhang 1%. The only relay without a majority favorite was the women’s 4X100 medley. There gold medal picks had Australia 39%, USA 33%, China 20%, Sweden 8%.
-Nathan Adrian in the 100 free was the only individual seeded over 1% slower than first and picked to win gold by more than 25% of entries.
-8 swimmers were seeded less than .3% behind first and picked to win gold by less than 25% of entries. Katinka Hosszu, Women’s 200 back, 18% picked to win gold; Bronte Campbell, Women’s 100 free, 5%; David Plummer, Men’s 100 back, 22%; Chad le Clos, Men’s 100 fly, 7%; Kosuke Hagino, Men’s 200 IM, 7%; Franziska Hentke, Women’s 200 Fly, 5%; Federica Pellegrini, Women’s 200 free, 3%; Paul Biedermann, Men’s 200 free, 5%.
In general, people rarely picked swimmers who weren’t seeded close to the top to win. Here a look at how often 2nd and 3rd seeded swimmers were picked to win vs the % gap of their seed time to the top seed:
Here are the pick percentages for everyone who showed up in more than 5% of picks in an event:
| Gender | Event | Name | Country | Seed | Gold | Silver | Bronze | Medal |
| Women | 100 Back | Emily Seebohm | AUS | 58.26 | 94% | 4% | 2% | 100% |
| Women | 100 Back | Mie Nielsen | DEN | 58.73 | 1% | 33% | 21% | 55% |
| Women | 100 Back | Madison Wilson | AUS | 58.75 | 1% | 21% | 23% | 45% |
| Women | 100 Back | Katinka Hosszu | HUN | 58.78 | 3% | 32% | 21% | 56% |
| Women | 100 Back | Olivia Smoliga | USA | 59.02 | 1% | 8% | 23% | 32% |
| Women | 200 Back | Emily Seebohm | AUS | 2:05.81 | 62% | 26% | 9% | 97% |
| Women | 200 Back | Katinka Hosszu | HUN | 2:06.18 | 18% | 35% | 31% | 84% |
| Women | 200 Back | Missy Franklin | USA | 2:06.34 | 17% | 23% | 24% | 64% |
| Women | 200 Back | Belinda Hocking | AUS | 2:06.49 | 1% | 6% | 12% | 19% |
| Women | 200 Back | Maya Dirado | USA | 2:06.90 | 2% | 9% | 23% | 34% |
| Women | 100 Breast | Lilly King | USA | 1:05.20 | 59% | 36% | 3% | 98% |
| Women | 100 Breast | Ruta Meilutyte | LTU | 1:05.46 | 38% | 39% | 19% | 96% |
| Women | 100 Breast | Katie Meili | USA | 1:05.64 | 2% | 20% | 42% | 64% |
| Women | 100 Breast | Alia Atkinson | JAM | 1:05.93 | 0% | 3% | 29% | 32% |
| Women | 200 Breast | Viktoria Zeynep Gunes | TUR | 2:19.64 | 21% | 40% | 17% | 78% |
| Women | 200 Breast | Rie Kaneto | JPN | 2:19.65 | 60% | 25% | 9% | 94% |
| Women | 200 Breast | Kanako Watanabe | JPN | 2:20.90 | 12% | 21% | 37% | 70% |
| Women | 200 Breast | Taylor McKeown | AUS | 2:21.45 | 2% | 5% | 11% | 18% |
| Women | 200 Breast | Rikke Pedersen | DEN | 2:21.58 | 5% | 7% | 16% | 28% |
| Women | 200 Breast | Lilly King | USA | 2:24.03 | 0% | 1% | 5% | 6% |
| Women | 100 Fly | Sarah Sjostrom | SWE | 55.64 | 88% | 9% | 2% | 99% |
| Women | 100 Fly | Kelsi Worrell | USA | 56.48 | 9% | 54% | 26% | 89% |
| Women | 100 Fly | Xinyi Chen | CHN | 56.82 | 0% | 6% | 10% | 16% |
| Women | 100 Fly | Jeanette Ottesen | DEN | 56.83 | 0% | 6% | 17% | 23% |
| Women | 100 Fly | Emma McKeon | AUS | 56.89 | 0% | 2% | 5% | 7% |
| Women | 100 Fly | Dana Vollmer | USA | 56.9 | 2% | 22% | 35% | 59% |
| Women | 100 Fly | Penny Oleksiak | CAN | 56.99 | 0% | 2% | 5% | 7% |
| Women | 200 Fly | Madeline Groves | AUS | 2:05.41 | 38% | 27% | 17% | 82% |
| Women | 200 Fly | Natsumi Hoshi | JPN | 2:05.56 | 29% | 26% | 17% | 72% |
| Women | 200 Fly | Franziska Hentke | GER | 2:05.77 | 5% | 12% | 19% | 36% |
| Women | 200 Fly | Mireia Belmonte | ESP | 2:05.86 | 21% | 15% | 13% | 49% |
| Women | 200 Fly | Cammile Adams | USA | 2:06.33 | 6% | 15% | 29% | 50% |
| Women | 200 Fly | Yufei Zhang | CHN | 2:06.51 | 1% | 2% | 3% | 6% |
| Women | 50 Free | Cate Campbell | AUS | 23.84 | 90% | 8% | 2% | 100% |
| Women | 50 Free | Ranomi Kromowidjojo | NED | 24.07 | 4% | 29% | 30% | 63% |
| Women | 50 Free | Bronte Campbell | AUS | 24.12 | 2% | 40% | 21% | 63% |
| Women | 50 Free | Sarah Sjostrom | SWE | 24.17 | 2% | 20% | 28% | 50% |
| Women | 50 Free | Francesca Halsall | GBR | 24.21 | 0% | 0% | 5% | 5% |
| Women | 50 Free | Abbey Weitzeil | USA | 24.28 | 1% | 3% | 12% | 16% |
| Women | 100 Free | Cate Campbell | AUS | 52.38 | 92% | 6% | 2% | 100% |
| Women | 100 Free | Bronte Campbell | AUS | 52.52 | 5% | 69% | 19% | 93% |
| Women | 100 Free | Femke Heemskerk | NED | 52.69 | 0% | 4% | 14% | 18% |
| Women | 100 Free | Sarah Sjostrom | SWE | 52.7 | 2% | 19% | 54% | 75% |
| Women | 100 Free | Abbey Weitzeil | USA | 53.28 | 1% | 1% | 5% | 7% |
| Women | 200 Free | Sarah Sjostrom | SWE | 1:54.31 | 9% | 68% | 15% | 92% |
| Women | 200 Free | Katie Ledecky | USA | 1:54.43 | 88% | 10% | 2% | 100% |
| Women | 200 Free | Federica Pellegrini | ITA | 1:54.55 | 3% | 17% | 50% | 70% |
| Women | 200 Free | Femke Heemskerk | NED | 1:54.68 | 0% | 1% | 10% | 11% |
| Women | 200 Free | Emma McKeon | AUS | 1:54.83 | 0% | 2% | 12% | 14% |
| Women | 200 Free | Missy Franklin | USA | 1:55.49 | 0% | 2% | 10% | 12% |
| Women | 400 Free | Katie Ledecky | USA | 3:58.98 | 99% | 1% | 0% | 100% |
| Women | 400 Free | Leah Smith | USA | 4:00.65 | 1% | 95% | 3% | 99% |
| Women | 400 Free | Sharon Van Rouwendaal | NED | 4:03.02 | 0% | 2% | 23% | 25% |
| Women | 400 Free | Jessica Ashwood | AUS | 4:03.34 | 0% | 1% | 40% | 41% |
| Women | 400 Free | Boglarka Kapas | HUN | 4:03.47 | 0% | 0% | 11% | 11% |
| Women | 400 Free | Jazz Carlin | GBR | 4:03.51 | 0% | 0% | 7% | 7% |
| Women | 400 Free | Brittany MacLean | CAN | 4:03.84 | 0% | 0% | 10% | 10% |
| Women | 800 Free | Katie Ledecky | USA | 8:06.68 | 99% | 0% | 0% | 99% |
| Women | 800 Free | Lauren Boyle | NZL | 8:17.65 | 0% | 36% | 30% | 66% |
| Women | 800 Free | Jazz Carlin | GBR | 8:18.15 | 0% | 16% | 18% | 34% |
| Women | 800 Free | Jessica Ashwood | AUS | 8:18.41 | 0% | 24% | 15% | 39% |
| Women | 800 Free | Leah Smith | USA | 8:20.18 | 0% | 20% | 29% | 49% |
| Women | 200 IM | Katinka Hosszu | HUN | 2:06.12 | 95% | 4% | 1% | 100% |
| Women | 200 IM | Siobhan-Marie O’Connor | GBR | 2:08.45 | 1% | 23% | 59% | 83% |
| Women | 200 IM | Maya Dirado | USA | 2:08.99 | 4% | 70% | 23% | 97% |
| Women | 200 IM | Alicia Coutts | AUS | 2:09.95 | 0% | 1% | 7% | 8% |
| Women | 400 IM | Katinka Hosszu | HUN | 4:29.89 | 87% | 9% | 2% | 98% |
| Women | 400 IM | Maya Dirado | USA | 4:31.71 | 11% | 73% | 10% | 94% |
| Women | 400 IM | Hannah Miley | GBR | 4:32.16 | 1% | 8% | 26% | 35% |
| Women | 400 IM | Emily Overholt | CAN | 4:32.52 | 0% | 2% | 22% | 24% |
| Women | 400 IM | Mireia Belmonte | ESP | 4:33.42 | 0% | 3% | 19% | 22% |
| Women | 400 IM | Elizabeth Beisel | USA | 4:35.59 | 1% | 4% | 19% | 24% |
| Men | 100 Back | Mitchell Larkin | AUS | 52.11 | 16% | 48% | 34% | 98% |
| Men | 100 Back | David Plummer | USA | 52.12 | 22% | 27% | 44% | 93% |
| Men | 100 Back | Ryan Murphy | USA | 52.26 | 61% | 24% | 12% | 97% |
| Men | 100 Back | Camille Lacourt | FRA | 52.48 | 0% | 1% | 6% | 7% |
| Men | 100 Breast | Adam Peaty | GBR | 57.92 | 91% | 7% | 1% | 99% |
| Men | 100 Breast | Cameron van der Burgh | RSA | 58.49 | 4% | 54% | 32% | 90% |
| Men | 100 Breast | Kevin Cordes | USA | 58.94 | 5% | 36% | 45% | 86% |
| Men | 100 Breast | Giedrius Titenis | LTU | 58.96 | 0% | 0% | 7% | 7% |
| Men | 100 Breast | Joao Gomes Junior | BRA | 59.06 | 0% | 1% | 6% | 7% |
| Men | 100 Breast | Ross Murdoch | GBR | 59.09 | 0% | 1% | 5% | 6% |
| Men | 100 Fly | Michael Phelps | USA | 50.45 | 89% | 7% | 3% | 99% |
| Men | 100 Fly | Chad le Clos | RSA | 50.56 | 7% | 57% | 23% | 87% |
| Men | 100 Fly | Laszlo Cseh | HUN | 50.86 | 1% | 21% | 23% | 45% |
| Men | 100 Fly | Joseph Schooling | SIN | 50.96 | 1% | 13% | 40% | 54% |
| Men | 100 Fly | Tom Shields | USA | 51.03 | 0% | 1% | 10% | 11% |
| Men | 100 Free | Cameron McEvoy | AUS | 47.04 | 71% | 26% | 3% | 100% |
| Men | 100 Free | Nathan Adrian | USA | 47.72 | 27% | 63% | 7% | 97% |
| Men | 100 Free | Zetao Ning | CHN | 47.84 | 2% | 7% | 27% | 36% |
| Men | 100 Free | Luca Dotto | ITA | 47.96 | 0% | 2% | 10% | 12% |
| Men | 100 Free | Jeremy Stravius | FRA | 47.97 | 0% | 0% | 12% | 12% |
| Men | 100 Free | Santo Condorelli | CAN | 47.98 | 0% | 1% | 25% | 26% |
| Men | 100 Free | Caeleb Dressel | USA | 48.23 | 0% | 0% | 9% | 9% |
| Men | 1500 Free | Gregorio Paltrinieri | ITA | 14:34.04 | 71% | 21% | 5% | 97% |
| Men | 1500 Free | Mack Horton | AUS | 14:39.54 | 6% | 32% | 36% | 74% |
| Men | 1500 Free | Connor Jaeger | USA | 14:41.20 | 7% | 23% | 44% | 74% |
| Men | 1500 Free | Gabriele Detti | ITA | 14:46.48 | 0% | 1% | 4% | 5% |
| Men | 1500 Free | Ryan Cochrane | CAN | 14:51.08 | 1% | 1% | 4% | 6% |
| Men | 1500 Free | Yang Sun | CHN | 14:55.11 | 14% | 21% | 4% | 39% |
| Men | 200 Back | Mitchell Larkin | AUS | 1:53.17 | 55% | 41% | 2% | 98% |
| Men | 200 Back | Ryan Murphy | USA | 1:53.95 | 44% | 53% | 3% | 100% |
| Men | 200 Back | Evgeny Rylov | RUS | 1:54.21 | 0% | 2% | 22% | 24% |
| Men | 200 Back | Radoslaw Kawecki | POL | 1:54.55 | 0% | 1% | 18% | 19% |
| Men | 200 Back | Jacob Pebley | USA | 1:54.77 | 0% | 2% | 36% | 38% |
| Men | 200 Back | Ryosuke Irie | JPN | 1:54.81 | 0% | 1% | 17% | 18% |
| Men | 200 Breast | Josh Prenot | USA | 2:07.17 | 61% | 21% | 10% | 92% |
| Men | 200 Breast | Marco Koch | GER | 2:07.69 | 18% | 25% | 25% | 68% |
| Men | 200 Breast | Yasuhiro Koseki | JPN | 2:07.77 | 2% | 18% | 15% | 35% |
| Men | 200 Breast | Kevin Cordes | USA | 2:07.81 | 13% | 24% | 32% | 69% |
| Men | 200 Breast | Daniel Gyurta | HUN | 2:08.10 | 5% | 10% | 13% | 28% |
| Men | 200 Fly | Laszlo Cseh | HUN | 1:52.91 | 21% | 55% | 22% | 98% |
| Men | 200 Fly | Michael Phelps | USA | 1:52.94 | 75% | 16% | 9% | 100% |
| Men | 200 Fly | Chad le Clos | RSA | 1:53.68 | 4% | 27% | 62% | 93% |
| Men | 200 Free | James Guy | GBR | 1:45.14 | 23% | 43% | 15% | 81% |
| Men | 200 Free | Yang Sun | CHN | 1:45.20 | 59% | 16% | 8% | 83% |
| Men | 200 Free | Paul Biedermann | GER | 1:45.38 | 5% | 7% | 8% | 20% |
| Men | 200 Free | Kosuke Hagino | JPN | 1:45.50 | 2% | 9% | 19% | 30% |
| Men | 200 Free | Thomas Fraser-Holmes | AUS | 1:45.63 | 1% | 2% | 4% | 7% |
| Men | 200 Free | Townley Haas | USA | 1:45.66 | 6% | 10% | 16% | 32% |
| Men | 200 Free | Conor Dwyer | USA | 1:45.67 | 2% | 10% | 24% | 36% |
| Men | 200 Free | Yannick Agnel | FRA | 1:45.97 | 2% | 1% | 3% | 6% |
| Men | 200 IM | Michael Phelps | USA | 1:54.75 | 87% | 12% | 1% | 100% |
| Men | 200 IM | Kosuke Hagino | JPN | 1:55.07 | 7% | 38% | 51% | 96% |
| Men | 200 IM | Ryan Lochte | USA | 1:55.81 | 6% | 49% | 39% | 94% |
| Men | 200 IM | Thiago Pereira | BRA | 1:56.65 | 0% | 0% | 9% | 9% |
| Men | 400 Free | Mack Horton | AUS | 3:41.65 | 37% | 46% | 9% | 92% |
| Men | 400 Free | Yang Sun | CHN | 3:42.58 | 56% | 26% | 7% | 89% |
| Men | 400 Free | James Guy | GBR | 3:43.75 | 3% | 14% | 22% | 39% |
| Men | 400 Free | Connor Jaeger | USA | 3:43.79 | 3% | 10% | 47% | 60% |
| Men | 400 Free | Tae Hwan Park | KOR | 3:44.26 | 0% | 1% | 6% | 7% |
| Men | 400 IM | Daiya Seto | JPN | 4:08.50 | 17% | 53% | 26% | 96% |
| Men | 400 IM | Kosuke Hagino | JPN | 4:08.54 | 71% | 14% | 11% | 96% |
| Men | 400 IM | Chase Kalisz | USA | 4:09.54 | 12% | 29% | 50% | 91% |
| Men | 400 IM | David Verraszto | HUN | 4:09.90 | 0% | 1% | 6% | 7% |
| Men | 400 IM | Jay Litherland | USA | 4:11.02 | 0% | 1% | 4% | 5% |
| Men | 50 Free | Florent Manaudou | FRA | 21.19 | 69% | 22% | 6% | 97% |
| Men | 50 Free | Nathan Adrian | USA | 21.37 | 25% | 47% | 23% | 95% |
| Men | 50 Free | Cameron McEvoy | AUS | 21.44 | 4% | 17% | 23% | 44% |
| Men | 50 Free | Bruno Fratus | BRA | 21.5 | 1% | 9% | 24% | 34% |
| Men | 50 Free | Anthony Ervin | USA | 21.52 | 1% | 4% | 22% | 27% |
| Men | 4X100 MR | USA | 3:29.93 | 96% | 3% | 1% | 100% | |
| Men | 4X100 MR | Australia | 3:30.08 | 2% | 74% | 17% | 93% | |
| Men | 4X100 MR | France | 3:30.50 | 1% | 13% | 31% | 45% | |
| Men | 4X100 MR | Great Britain | 3:30.67 | 1% | 8% | 39% | 48% | |
| Men | 4X100 MR | Japan | 3:31.10 | 0% | 1% | 7% | 8% | |
| Men | 4X200 FR | Great Britain | 7:04.33 | 4% | 50% | 39% | 93% | |
| Men | 4X200 FR | USA | 7:04.75 | 94% | 5% | 1% | 100% | |
| Men | 4X200 FR | Australia | 7:05.34 | 1% | 43% | 51% | 95% | |
| Men | 4X100 FR | France | 3:10.74 | 39% | 28% | 27% | 94% | |
| Men | 4X100 FR | Russia | 3:11.19 | 2% | 8% | 10% | 20% | |
| Men | 4X100 FR | Italy | 3:12.53 | 0% | 9% | 10% | 19% | |
| Men | 4X100 FR | Brazil | 3:13.22 | 1% | 4% | 17% | 22% | |
| Men | 4X100 FR | USA | 3:16.01 | 40% | 28% | 19% | 87% | |
| Men | 4X100 FR | Australia | 3:12.26 | 17% | 22% | 16% | 55% | |
| Women | 4X100 MR | China | 3:54.41 | 20% | 24% | 34% | 78% | |
| Women | 4X100 MR | Sweden | 3:55.24 | 8% | 12% | 21% | 41% | |
| Women | 4X100 MR | Australia | 3:55.56 | 39% | 31% | 17% | 87% | |
| Women | 4X100 MR | USA | 3:56.76 | 33% | 32% | 22% | 87% | |
| Women | 4X200 FR | USA | 7:45.37 | 98% | 2% | 1% | 100% | |
| Women | 4X200 FR | Italy | 7:48.41 | 0% | 33% | 32% | 65% | |
| Women | 4X200 FR | China | 7:49.10 | 0% | 38% | 27% | 65% | |
| Women | 4X200 FR | Sweden | 7:50.24 | 0% | 9% | 26% | 35% | |
| Women | 4X200 FR | Australia | 7:51.02 | 1% | 16% | 11% | 28% | |
| Women | 4X100 FR | Australia | 3:31.48 | 94% | 5% | 1% | 100% | |
| Women | 4X100 FR | Netherlands | 3:33.67 | 1% | 33% | 57% | 91% | |
| Women | 4X100 FR | USA | 3:34.61 | 5% | 60% | 31% | 96% | |
| Women | 4X100 FR | Sweden | 3:35.71 | 0% | 2% | 6% | 8% | |
| Women | 4X100 FR | Canada | 3:36.44 | 0% | 0% | 5% | 5% |
Pac 12 Olympians at Rio. Can’t see a thread on this topic so I thought I’d post it here. Of the thousands of athletes at the 2016 Rio Olympics, which schools and conferences are the big contributors of those Olympians?. CBS Sports has the Pac 12 and specifically the big California schools as the top 4. But this list includes coaches as Olympians. If it was just athletes the Pac 12 would have 4 of the top 5 places — USC with 44, Cal with 41, Stanford with 39, Florida with 31 an UCLA with 29. USC has a strong international flavor with those 44 athletes coming from 21 countries in 9 sports. Since this is the Summer Olympics, you’d… Read more »
Pac-12 Dominates Olympians at Rio
Any chance you’ll have a spreadsheet with everyone’s picks again? I can’t access my picks and now I need to remember who I picked and who I should root for…
Americans certainly are optimists! 😉
Excited to see how my picks do! As always, I’m optimistic about the Canadians but hopefully they live up to my high expectations.
Will you keep track of how picking the top seeded entrants in each events would do? I like using that as a baseline for how well I’m doing!
Medal tables are based on gold medals. The most important for a nation is to win gold medals if they want to be ranked high.
USA won the amazing number of 16 golds in London out of 32 events in the pool.
I take advantage of that article to post my last predictions about winners.
And as usual I’ve made changes compared to the last time…. 🙄
MEN
50 free. Florent Manaudou
100 free. Cameron McEvoy
200 free. Sun Yang
400 free. Sun Yang
1500 free. Gregorio Paltrinieri
100 back. Ryan Murphy
200 back. Mitch Larkin
100 breast. Adam Peaty
200 breast. Josh Prenot
100 fly. Chad le… Read more »
I’m so glad that you I’ve finally agreed with me that USA will win 10 golds in swimming.
Previously you predicted 7 golds.
Welcome to the club, Bobo!
Very interesting picks, especially for athletics …
Roleder in womens 100m hurdles? Pretty brave, considering the american dominance.
Rypakova in womens triple jumps? I dont see her beating Rojas or Ibarguen and for sure not both.
Schwanitz over Adams and Gong in womens shot put? I picked her for bronze.
Molitor for sure wont win womens javelin throw, she hasnt even been nominated …
I think gold will go to the girl from Belarus.
KJT over JEH and BTE in womens heptathlon? That would be a huge surprise.
I think your predictions on the mens side are much better. I dont agree about Malachowski beating Harting and Yego beating Röhler.
About swimming:… Read more »
cool analysis! thanks for putting that together.
Have the start lists for prelims been released? I mostly want to see the us relays order/who’s on it
They won’t release that until race day
It is race day…
I said relays but I meant only the women’s 400 free relay