What this team's results have earned: every match in the database is replayed in date order, both sides start at 1500 and the winner takes points from the loser. The rating is the one it held after its last rated match, and the rank counts every club ever rated, sides that no longer play included. A measure of strength, not a forecast of the next result. Computed 3 Nov 2026.
| # | Run | From → To | |
|---|---|---|---|
| 1 | 8 | 19 May 2024 → 29 Jun 2024 | ▸ matches |
| 2 | 7 | 25 Apr 2025 → 25 May 2025 | ▸ matches |
| 3 | 6 | 16 Jul 2025 → 23 Aug 2025 | ▸ matches |
| 4 | 6 | 06 Jun 2018 → 08 Dec 2018 | ▸ matches |
| 5 | 5 | 10 Jul 2024 → 11 Aug 2024 | ▸ matches |
| 6 | 4 | 11 Jun 2025 → 29 Jun 2025 | ▸ matches |
| 7 | 4 | 16 Feb 2025 → 02 Mar 2025 | ▸ matches |
| 8 | 4 | 25 Aug 2024 → 22 Sep 2024 | ▸ matches |
| 9 | 4 | 12 Dec 2004 → 01 Jan 2005 | ▸ matches |
| 10 | 3 | 19 Sep 2026 → 17 Oct 2026 | ▸ matches |
| Competition | P | D | Draw% | N | Max |
|---|---|---|---|---|---|
| J1 League | 90 | 28 | 31.1% | 1 | 7 |
| Emperor's Cup | 49 | 5 | 10.2% | 3 | 4 |
| Year | P | D | Draw% | Max |
|---|---|---|---|---|
| 2026 | 11 | 4 | 36.4% | 3 |
| 2025 | 41 | 10 | 24.4% | 7 |
| 2024 | 40 | 14 | 35.0% | 8 |
| 2023 | 2 | 1 | 50.0% | 1 |
| 2022 | 4 | 1 | 25.0% | 2 |
| 2021 | 1 | 0 | 0.0% | 1 |
| 2019 | 1 | 0 | 0.0% | 1 |
| 2018 | 6 | 0 | 0.0% | 6 |
| 2017 | 1 | 0 | 0.0% | 1 |
| 2016 | 3 | 0 | 0.0% | 3 |
| 2015 | 2 | 0 | 0.0% | 2 |
| 2014 | 1 | 0 | 0.0% | 1 |
| 2013 | 2 | 0 | 0.0% | 2 |
| 2012 | 2 | 0 | 0.0% | 2 |
| 2011 | 2 | 0 | 0.0% | 2 |
| 2010 | 2 | 0 | 0.0% | 2 |
| 2009 | 1 | 0 | 0.0% | 1 |
| 2008 | 1 | 0 | 0.0% | 1 |
| 2007 | 1 | 1 | 100.0% | 0 |
| 2006 | 1 | 0 | 0.0% | 1 |
| 2005 | 2 | 0 | 0.0% | 1 |
| 2004 | 3 | 0 | 0.0% | 3 |
| 2003 | 2 | 0 | 0.0% | 2 |
| 1999 | 1 | 0 | 0.0% | 1 |
| 1998 | 1 | 1 | 100.0% | 0 |
| 1997 | 1 | 0 | 0.0% | 1 |
| 1993 | 3 | 1 | 33.3% | 2 |
| 1992 | 1 | 0 | 0.0% | 1 |
Over 112 matches (Aug 2015 – Oct 2026), Tokyo Verdy drew 30 where the draw model expected 29.2 from those particular fixtures — about 1 more, or 0.2 standard errors, which is what the model expected, near enough.
A flat league average would have expected 26.7 instead — "more draws than the league" and "more draws than these fixtures deserved" are different claims. These matches were part of the model's own training set, so its chances were fitted already knowing the results.