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 | 21 | 27 Jan 2021 → 31 Jul 2021 | ▸ matches |
| 2 | 15 | 23 Aug 2014 → 13 Dec 2014 | ▸ matches |
| 3 | 14 | 14 Aug 2021 → 03 Dec 2021 | ▸ matches |
| 4 | 11 | 20 Apr 2018 → 15 Sep 2018 | ▸ matches |
| 5 | 11 | 14 Oct 2017 → 20 Dec 2017 | ▸ matches |
| 6 | 10 | 19 Apr 2019 → 31 Aug 2019 | ▸ matches |
| 7 | 10 | 20 Jan 2019 → 03 Mar 2019 | ▸ matches |
| 8 | 10 | 09 Apr 2016 → 10 Sep 2016 | ▸ matches |
| 9 | 10 | 07 Aug 2015 → 17 Oct 2015 | ▸ matches |
| 10 | 9 | 20 Mar 2009 → 15 May 2009 | ▸ matches |
| Competition | P | D | Draw% | N | Max |
|---|---|---|---|---|---|
| Ligue 2 | 505 | 162 | 32.1% | 6 | 14 |
| Ligue 1 | 218 | 56 | 25.7% | 18 | 18 |
| Coupe de France | 35 | 7 | 20.0% | 0 | 4 |
| Club Friendlies | 3 | 2 | 66.7% | 0 | 1 |
| Year | P | D | Draw% | Max |
|---|---|---|---|---|
| 2026 | 13 | 5 | 38.5% | 4 |
| 2024 | 1 | 1 | 100.0% | 0 |
| 2023 | 21 | 6 | 28.6% | 6 |
| 2022 | 36 | 12 | 33.3% | 6 |
| 2021 | 42 | 6 | 14.3% | 21 |
| 2020 | 30 | 10 | 33.3% | 4 |
| 2019 | 43 | 9 | 20.9% | 10 |
| 2018 | 39 | 11 | 28.2% | 11 |
| 2017 | 40 | 9 | 22.5% | 11 |
| 2016 | 38 | 13 | 34.2% | 10 |
| 2015 | 43 | 11 | 25.6% | 10 |
| 2014 | 41 | 12 | 29.3% | 15 |
| 2013 | 39 | 14 | 35.9% | 7 |
| 2012 | 40 | 12 | 30.0% | 5 |
| 2011 | 38 | 9 | 23.7% | 8 |
| 2010 | 38 | 12 | 31.6% | 7 |
| 2009 | 43 | 14 | 32.6% | 9 |
| 2008 | 42 | 14 | 33.3% | 5 |
| 2007 | 38 | 14 | 36.8% | 5 |
| 2006 | 39 | 11 | 28.2% | 8 |
| 2005 | 38 | 16 | 42.1% | 4 |
| 2004 | 19 | 6 | 31.6% | 6 |
Over 346 matches (Jan 2015 – Oct 2026), Dijon FCO drew 93 where the draw model expected 95.7 from those particular fixtures — about 3 fewer, or 0.3 standard errors, which is what the model expected, near enough.
A flat league average would have expected 99.1 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.