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 4 Nov 2026.
| # | Run | From → To | |
|---|---|---|---|
| 1 | 14 | 12 May 2019 → 17 Aug 2019 | ▸ matches |
| 2 | 14 | 02 Jul 2016 → 22 Sep 2016 | ▸ matches |
| 3 | 11 | 11 Aug 2024 → 03 Nov 2024 | ▸ matches |
| 4 | 11 | 20 Mar 2016 → 29 May 2016 | ▸ matches |
| 5 | 8 | 14 May 2022 → 26 Jun 2022 | ▸ matches |
| 6 | 8 | 13 Sep 2020 → 18 Oct 2020 | ▸ matches |
| 7 | 8 | 18 Jul 2020 → 23 Aug 2020 | ▸ matches |
| 8 | 8 | 14 Apr 2013 → 25 May 2013 | ▸ matches |
| 9 | 7 | 23 Aug 2025 → 03 Oct 2025 | ▸ matches |
| 10 | 7 | 16 Mar 2025 → 25 Apr 2025 | ▸ matches |
| Competition | P | D | Draw% | N | Max |
|---|---|---|---|---|---|
| J1 League | 387 | 103 | 26.6% | 4 | 13 |
| Emperor's Cup | 48 | 11 | 22.9% | 2 | 3 |
| Club Friendlies | 1 | 0 | 0.0% | 1 | 1 |
| Year | P | D | Draw% | Max |
|---|---|---|---|---|
| 2026 | 1 | 0 | 0.0% | 1 |
| 2025 | 40 | 8 | 20.0% | 7 |
| 2024 | 41 | 9 | 22.0% | 11 |
| 2023 | 38 | 11 | 29.0% | 5 |
| 2022 | 36 | 11 | 30.6% | 8 |
| 2021 | 41 | 18 | 43.9% | 5 |
| 2020 | 34 | 9 | 26.5% | 8 |
| 2019 | 36 | 7 | 19.4% | 14 |
| 2018 | 37 | 12 | 32.4% | 7 |
| 2017 | 2 | 1 | 50.0% | 1 |
| 2016 | 38 | 7 | 18.4% | 14 |
| 2015 | 36 | 9 | 25.0% | 6 |
| 2014 | 2 | 1 | 50.0% | 1 |
| 2013 | 36 | 8 | 22.2% | 8 |
| 2012 | 2 | 0 | 0.0% | 2 |
| 2011 | 4 | 1 | 25.0% | 2 |
| 2010 | 2 | 0 | 0.0% | 2 |
| 2009 | 1 | 0 | 0.0% | 1 |
| 2008 | 1 | 1 | 100.0% | 0 |
| 2007 | 2 | 0 | 0.0% | 2 |
| 2006 | 2 | 0 | 0.0% | 2 |
| 2005 | 1 | 1 | 100.0% | 0 |
| 2004 | 1 | 0 | 0.0% | 1 |
| 2003 | 1 | 0 | 0.0% | 1 |
| 1995 | 1 | 0 | 0.0% | 1 |
Over 380 matches (Mar 2015 – Aug 2026), Shonan Bellmare drew 102 where the draw model expected 97.5 from those particular fixtures — about 4 more, or 0.5 standard errors, which is what the model expected, near enough.
A flat league average would have expected 93.1 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.