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Mwangas Jano's best meet by DOTS to date came in 2022 at age 46 in the 140 kg class: 817.5 kg at 452.6 DOTS. Their total grew 165 kg over 8.9 years between their first meet and that mark (~18.48 kg/year). Career variance was 66% squat-driven.
Career-best meet (by DOTS): Heavy Iron Classic · WRPF
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| Date | Meet | Equipment | Squat (kg) | Bench (kg) | Deadlift (kg) | Total (kg) | DOTS |
|---|---|---|---|---|---|---|---|
| 2013-12-07 | 60th IronMan Powerlifting & Benchpress Championships | Wraps | 257.5 | 157.5 | 237.5 | 652.5 | 376.44 |
| 2014-10-18 | Central California Open Powerlifting Championships | Raw | 252.5 | 160 | 227.5 | 640 | 367.63 |
| 2015-02-14 | Valentine's Push-Pull | Raw | — | 170 | 235 | — | — |
| 2016-08-06 | NASPOWER Record Breaker Powerlifting Championship | Wraps | 290 | -162.5 | — | — | — |
| 2016-10-15 | Central California Open Powerlifting Championships | Raw | 275 | 152.5 | 245 | 672.5 | 382.21 |
| 2017-04-01 | Drug Tested California State Powerlifting Championships | Wraps | 277.5 | 157.5 | 260 | 695 | 395.93 |
| 2018-06-09 | Ikaika Warrior Powerlifting Championship | Wraps | 295 | 160 | 277.5 | 732.5 | 418.17 |
| 2019-06-08 | Drug Tested Ikaika Warrior Powerlifting Championship | Wraps | 300 | 157.5 | 270 | 727.5 | 413.26 |
| 2020-08-01 | NASPOWER Championship | Wraps | 320 | 182.5 | 270 | 772.5 | 428.31 |
| 2021-04-17 | Iron Office Spring Showdown | Wraps | 320 | 187.5 | 265 | 772.5 | 428.82 |
| 2021-10-09 | Valley's Fall Classic | Wraps | 330 | 182.5 | 290 | 802.5 | 444.75 |
| 2022-11-12 | Heavy Iron Classic | Wraps | 342.5 | 187.5 | 287.5 | 817.5 | 452.58 |
| 2024-03-30 | Hi TS March Madness | Wraps | 345 | 172.5 | 295 | 812.5 | 452.58 |
Showing the most recent 3 and career-best meet. Open the full ledger to see every meet, grouped by year.
vs Wraps · 140 kg class · masters-1 · USA · drug-tested + not tested
vs Wraps · 140 kg class · masters-1 · drug-tested + not tested
DOTS ranks across all weight classes — matching Best Lifter scoring — while Squat, Bench, Deadlift, and Total rank within the cohort named under each radar.