{
  "id": 522309,
  "title": "Extended leaderboard with more evaluation metrics (updated 25th July)",
  "url": "/competitions/the-future-crop-challenge/discussion/522309",
  "author_name": "Lily-belle Sweet",
  "post_date": "2024-07-25T13:36:37.623000",
  "votes": 2,
  "comment_count": 0,
  "views": 0,
  "content": "<p><strong>There was an error in the code producing the leaderboard previously! Thanks to Monique for spotting this. The names of the participant were correct, but the submission numbers were not.</strong></p>\n<p>We're not only looking for the best performance in terms of RMSE, but also in terms of how well the models can capture the variability of annual production in breadbasket regions (Iowa for maize, Germany for wheat). Furthermore, as we find that often models overfit spatially but don't manage to get the temporal variability at each gridcell, we also measure the median R2 over all gridcells.</p>\n<p>Starting this week, we plan to calculate the scores on these metrics for the validation years (2020-2050) and share the results at ~weekly intervals, so you can see how well your models are performing.</p>\n<p>The number next to your first name or initial indicates which of your submissions this represents - 1 would be the first you submitted, etc. Bold denotes the top three entries for that particular metric.</p>\n<p>Should we consider other metrics as well? Interested in your thoughts!</p>\n<p><strong>Don't forget - to enter the competition it's compulsory to share your code. Please make your notebooks public or contact us to share!</strong></p>\n<table>\n<thead>\n<tr>\n<th>**Submission</th>\n<th>Validation Median R2</th>\n<th>Validation Iowa R2</th>\n<th>Validation Germany R2**</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td><strong>Abdelghani32</strong></td>\n<td>0.0984</td>\n<td>0.5723</td>\n<td>0.1124</td>\n</tr>\n<tr>\n<td><strong>Abdelghani34</strong></td>\n<td>0.0983</td>\n<td>0.5676</td>\n<td>0.125</td>\n</tr>\n<tr>\n<td><strong>Abdelghani33</strong></td>\n<td>0.0958</td>\n<td>0.561</td>\n<td>0.1342</td>\n</tr>\n<tr>\n<td><strong>Monique22</strong></td>\n<td>0.0795</td>\n<td>0.5541</td>\n<td>0.136</td>\n</tr>\n<tr>\n<td><strong>Abdelghani31</strong></td>\n<td>0.075</td>\n<td>0.5738</td>\n<td>0.1084</td>\n</tr>\n<tr>\n<td>Abdelghani28</td>\n<td>0.0744</td>\n<td>0.5737</td>\n<td>0.1032</td>\n</tr>\n<tr>\n<td>Abdelghani30</td>\n<td>0.0703</td>\n<td>0.5717</td>\n<td>0.0977</td>\n</tr>\n<tr>\n<td>Abdelghani29</td>\n<td>0.0702</td>\n<td>0.5721</td>\n<td>0.1133</td>\n</tr>\n<tr>\n<td>Monique18</td>\n<td>0.0532</td>\n<td>0.5629</td>\n<td>0.1219</td>\n</tr>\n<tr>\n<td>Abdelghani27</td>\n<td>0.051</td>\n<td>0.617</td>\n<td>0.115</td>\n</tr>\n<tr>\n<td>Abdelghani24</td>\n<td>0.043</td>\n<td>0.5921</td>\n<td>0.1183</td>\n</tr>\n<tr>\n<td>Abdelghani25</td>\n<td>0.0392</td>\n<td>0.6169</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Abdelghani23</td>\n<td>0.0351</td>\n<td>0.5755</td>\n<td>0.1082</td>\n</tr>\n<tr>\n<td>Abdelghani26</td>\n<td>0.0326</td>\n<td>0.5643</td>\n<td>0.0935</td>\n</tr>\n<tr>\n<td>Abdelghani22</td>\n<td>0.005</td>\n<td>0.5333</td>\n<td>0.0645</td>\n</tr>\n<tr>\n<td>Abdelghani16</td>\n<td>0.0027</td>\n<td>0.5814</td>\n<td>0.1255</td>\n</tr>\n<tr>\n<td>Abdelghani15</td>\n<td>-0.0019</td>\n<td>0.576</td>\n<td>0.1159</td>\n</tr>\n<tr>\n<td>Johannes22</td>\n<td>-0.0066</td>\n<td>-0.1648</td>\n<td>0.1255</td>\n</tr>\n<tr>\n<td>Monique19</td>\n<td>-0.0067</td>\n<td>0.1688</td>\n<td>0.1374</td>\n</tr>\n<tr>\n<td>Johannes16</td>\n<td>-0.0123</td>\n<td>-0.6302</td>\n<td>-0.0297</td>\n</tr>\n<tr>\n<td>Abdelghani13</td>\n<td>-0.0134</td>\n<td>0.5699</td>\n<td>0.1058</td>\n</tr>\n<tr>\n<td>Johannes12</td>\n<td>-0.0168</td>\n<td>-0.2099</td>\n<td>-0.0358</td>\n</tr>\n<tr>\n<td>Johannes19</td>\n<td>-0.0176</td>\n<td>0.0521</td>\n<td>0.0434</td>\n</tr>\n<tr>\n<td>Johannes17</td>\n<td>-0.0185</td>\n<td>-0.1494</td>\n<td>-0.0392</td>\n</tr>\n<tr>\n<td>Abdelghani17</td>\n<td>-0.0199</td>\n<td>0.5984</td>\n<td>0.1719</td>\n</tr>\n<tr>\n<td>Johannes21</td>\n<td>-0.0214</td>\n<td>-0.6362</td>\n<td>-0.0465</td>\n</tr>\n<tr>\n<td>Abdelghani14</td>\n<td>-0.0239</td>\n<td>0.5631</td>\n<td>0.0951</td>\n</tr>\n<tr>\n<td>Johannes18</td>\n<td>-0.0291</td>\n<td>-0.8114</td>\n<td>0.117</td>\n</tr>\n<tr>\n<td>Johannes20</td>\n<td>-0.0359</td>\n<td>-0.2832</td>\n<td>-0.0131</td>\n</tr>\n<tr>\n<td>Abdelghani19</td>\n<td>-0.0387</td>\n<td>0.5556</td>\n<td>0.0839</td>\n</tr>\n<tr>\n<td>Abdelghani12</td>\n<td>-0.0387</td>\n<td>0.5556</td>\n<td>0.0839</td>\n</tr>\n<tr>\n<td>Abdelghani18</td>\n<td>-0.0413</td>\n<td>0.4869</td>\n<td>0.0855</td>\n</tr>\n<tr>\n<td>Johannes15</td>\n<td>-0.0418</td>\n<td>-0.345</td>\n<td>0.0767</td>\n</tr>\n<tr>\n<td>Johannes14</td>\n<td>-0.0448</td>\n<td>-0.6308</td>\n<td>0.08</td>\n</tr>\n<tr>\n<td>Abdelghani20</td>\n<td>-0.0693</td>\n<td>0.4633</td>\n<td>0.064</td>\n</tr>\n<tr>\n<td>Abdelghani21</td>\n<td>-0.1319</td>\n<td>0.4343</td>\n<td>0.0658</td>\n</tr>\n<tr>\n<td>Monique17</td>\n<td>-0.1639</td>\n<td><strong>0.7599</strong></td>\n<td><strong>0.1983</strong></td>\n</tr>\n<tr>\n<td>K2</td>\n<td>-0.1658</td>\n<td>0.4537</td>\n<td><strong>0.235</strong></td>\n</tr>\n<tr>\n<td>K1</td>\n<td>-0.1658</td>\n<td>0.4537</td>\n<td><strong>0.235</strong></td>\n</tr>\n<tr>\n<td>Divya1</td>\n<td>-0.1808</td>\n<td>0.4543</td>\n<td>0.1801</td>\n</tr>\n<tr>\n<td>Johannes13</td>\n<td>-0.1906</td>\n<td>-0.717</td>\n<td>0.01</td>\n</tr>\n<tr>\n<td>Abdelghani5</td>\n<td>-0.2021</td>\n<td>-0.5034</td>\n<td>-0.0258</td>\n</tr>\n<tr>\n<td>Monique20</td>\n<td>-0.2307</td>\n<td>-0.7257</td>\n<td>-0.0181</td>\n</tr>\n<tr>\n<td>Divya2</td>\n<td>-0.2443</td>\n<td>0.2476</td>\n<td>0.1434</td>\n</tr>\n<tr>\n<td>Abdelghani8</td>\n<td>-0.2712</td>\n<td>-0.5237</td>\n<td>-0.0151</td>\n</tr>\n<tr>\n<td>Abdelghani7</td>\n<td>-0.2722</td>\n<td>-0.5479</td>\n<td>-0.2447</td>\n</tr>\n<tr>\n<td>Lilybelle4</td>\n<td>-0.3237</td>\n<td>0.4267</td>\n<td>0.0434</td>\n</tr>\n<tr>\n<td>Johannes10</td>\n<td>-0.3239</td>\n<td>0.2614</td>\n<td>-0.3375</td>\n</tr>\n<tr>\n<td>Monique12</td>\n<td>-0.3302</td>\n<td>0.5687</td>\n<td><strong>0.2064</strong></td>\n</tr>\n<tr>\n<td>Monique16</td>\n<td>-0.3341</td>\n<td><strong>0.7025</strong></td>\n<td>0.1672</td>\n</tr>\n<tr>\n<td>Monique21</td>\n<td>-0.3373</td>\n<td>-2.794</td>\n<td>-0.0167</td>\n</tr>\n<tr>\n<td>Abdelghani10</td>\n<td>-0.3422</td>\n<td>0.5622</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Abdelghani11</td>\n<td>-0.3422</td>\n<td>0.5622</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Lilybelle2</td>\n<td>-0.3586</td>\n<td>-2.8099</td>\n<td>-0.0279</td>\n</tr>\n<tr>\n<td>Monique10</td>\n<td>-0.3655</td>\n<td>0.6148</td>\n<td><strong>0.2401</strong></td>\n</tr>\n<tr>\n<td>Johannes11</td>\n<td>-0.3713</td>\n<td>-2.3285</td>\n<td>0.0249</td>\n</tr>\n<tr>\n<td>Jonathan4</td>\n<td>-0.457</td>\n<td>-3.7363</td>\n<td>0.0177</td>\n</tr>\n<tr>\n<td>Jonathan1</td>\n<td>-0.4632</td>\n<td>-3.6195</td>\n<td>0.0592</td>\n</tr>\n<tr>\n<td>Jonathan2</td>\n<td>-0.4632</td>\n<td>-3.6195</td>\n<td>0.0592</td>\n</tr>\n<tr>\n<td>Johannes9</td>\n<td>-0.4742</td>\n<td>-0.0028</td>\n<td><strong>0.2706</strong></td>\n</tr>\n<tr>\n<td>Jonathan3</td>\n<td>-0.4874</td>\n<td>-3.6378</td>\n<td>0.0373</td>\n</tr>\n<tr>\n<td>Monique1</td>\n<td>-0.5523</td>\n<td><strong>0.6535</strong></td>\n<td>0.1653</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava4</td>\n<td>-0.5528</td>\n<td>0.6285</td>\n<td>0.1671</td>\n</tr>\n<tr>\n<td>Monique8</td>\n<td>-0.5618</td>\n<td>0.513</td>\n<td>-0.0133</td>\n</tr>\n<tr>\n<td>Monique7</td>\n<td>-0.5618</td>\n<td>0.513</td>\n<td>-0.0133</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava5</td>\n<td>-0.5768</td>\n<td><strong>0.7597</strong></td>\n<td>0.1903</td>\n</tr>\n<tr>\n<td>Monique6</td>\n<td>-0.5799</td>\n<td><strong>0.6531</strong></td>\n<td>0.0391</td>\n</tr>\n<tr>\n<td>Johannes8</td>\n<td>-0.6036</td>\n<td>-3.5369</td>\n<td>-0.042</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava3</td>\n<td>-0.6128</td>\n<td>0.4357</td>\n<td>0.0929</td>\n</tr>\n<tr>\n<td>Johannes6</td>\n<td>-0.6176</td>\n<td>0.3287</td>\n<td>-0.8237</td>\n</tr>\n<tr>\n<td>Johannes5</td>\n<td>-0.6176</td>\n<td>0.3287</td>\n<td>-0.8237</td>\n</tr>\n<tr>\n<td>Abdelghani6</td>\n<td>-0.6225</td>\n<td>-0.8669</td>\n<td>-0.3743</td>\n</tr>\n<tr>\n<td>Lilybelle3</td>\n<td>-0.6497</td>\n<td>0.3706</td>\n<td>0.0267</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava1</td>\n<td>-0.6527</td>\n<td>0.4069</td>\n<td>0.0403</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava2</td>\n<td>-0.6527</td>\n<td>0.4069</td>\n<td>0.0403</td>\n</tr>\n<tr>\n<td>Monique4</td>\n<td>-0.6833</td>\n<td>-0.0321</td>\n<td>-0.033</td>\n</tr>\n<tr>\n<td>Johannes2</td>\n<td>-0.6975</td>\n<td>-0.6625</td>\n<td>-2.1401</td>\n</tr>\n<tr>\n<td>JasonTarzan4</td>\n<td>-0.723</td>\n<td>0.148</td>\n<td>-0.008</td>\n</tr>\n<tr>\n<td>K6</td>\n<td>-0.7393</td>\n<td>0.453</td>\n<td>-12.0148</td>\n</tr>\n<tr>\n<td>Johannes1</td>\n<td>-0.7699</td>\n<td>-0.5199</td>\n<td>-1.4573</td>\n</tr>\n<tr>\n<td>Abdelghani9</td>\n<td>-0.7879</td>\n<td>0.003</td>\n<td>-0.069</td>\n</tr>\n<tr>\n<td>JasonTarzan3</td>\n<td>-0.7972</td>\n<td>0.1843</td>\n<td>0.1715</td>\n</tr>\n<tr>\n<td>JasonTarzan5</td>\n<td>-0.8373</td>\n<td>0.4139</td>\n<td>-0.0457</td>\n</tr>\n<tr>\n<td>K13</td>\n<td>-0.8707</td>\n<td>0.4459</td>\n<td>-19.0715</td>\n</tr>\n<tr>\n<td>K5</td>\n<td>-0.9618</td>\n<td>0.4275</td>\n<td>-15.2131</td>\n</tr>\n<tr>\n<td>Monique5</td>\n<td>-1.046</td>\n<td>-0.0292</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Jiang1</td>\n<td>-1.0538</td>\n<td>0.2185</td>\n<td>-0.4389</td>\n</tr>\n<tr>\n<td>Jiang2</td>\n<td>-1.0538</td>\n<td>0.2185</td>\n<td>-0.4389</td>\n</tr>\n<tr>\n<td>yuexiliuli18</td>\n<td>-1.1213</td>\n<td>-0.0236</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Monique15</td>\n<td>-1.1663</td>\n<td>-2.2257</td>\n<td>-6.7435</td>\n</tr>\n<tr>\n<td>K9</td>\n<td>-1.1718</td>\n<td>-2.6885</td>\n<td>-1.1253</td>\n</tr>\n<tr>\n<td>Johannes7</td>\n<td>-1.1726</td>\n<td>0.454</td>\n<td>-0.4443</td>\n</tr>\n<tr>\n<td>yuexiliuli25</td>\n<td>-1.1951</td>\n<td>-1.4452</td>\n<td>0.0314</td>\n</tr>\n<tr>\n<td>yuexiliuli17</td>\n<td>-1.2294</td>\n<td>-0.3931</td>\n<td>-1.1102</td>\n</tr>\n<tr>\n<td>K10</td>\n<td>-1.232</td>\n<td>-2.4394</td>\n<td>-1.8217</td>\n</tr>\n<tr>\n<td>Jiang6</td>\n<td>-1.2371</td>\n<td>0.5205</td>\n<td>-0.268</td>\n</tr>\n<tr>\n<td>JasonTarzan1</td>\n<td>-1.2402</td>\n<td>0.294</td>\n<td>-0.1699</td>\n</tr>\n<tr>\n<td>yuexiliuli16</td>\n<td>-1.2554</td>\n<td>0.1683</td>\n<td>-1.4837</td>\n</tr>\n<tr>\n<td>yuexiliuli20</td>\n<td>-1.296</td>\n<td>-0.5994</td>\n<td>-0.95</td>\n</tr>\n<tr>\n<td>K11</td>\n<td>-1.2995</td>\n<td>-5.5441</td>\n<td>-1.984</td>\n</tr>\n<tr>\n<td>yuexiliuli19</td>\n<td>-1.3151</td>\n<td>0.1852</td>\n<td>0.1641</td>\n</tr>\n<tr>\n<td>JasonTarzan2</td>\n<td>-1.3462</td>\n<td>-1.1281</td>\n<td>-0.6062</td>\n</tr>\n<tr>\n<td>Jiang7</td>\n<td>-1.4319</td>\n<td>-3.4144</td>\n<td>-0.122</td>\n</tr>\n<tr>\n<td>K8</td>\n<td>-1.4378</td>\n<td>-3.2419</td>\n<td>-1.2659</td>\n</tr>\n<tr>\n<td>RonvanBree2</td>\n<td>-1.4472</td>\n<td>0.4056</td>\n<td>-0.5598</td>\n</tr>\n<tr>\n<td>yuexiliuli21</td>\n<td>-1.4641</td>\n<td>-11.0763</td>\n<td>-0.291</td>\n</tr>\n<tr>\n<td>Monique3</td>\n<td>-1.5162</td>\n<td>-0.0122</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Monique2</td>\n<td>-1.5162</td>\n<td>-0.0122</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>yuexiliuli22</td>\n<td>-1.5375</td>\n<td>-7.5931</td>\n<td>-2.0214</td>\n</tr>\n<tr>\n<td>yuexiliuli14</td>\n<td>-1.5391</td>\n<td>-0.3425</td>\n<td>-1.0263</td>\n</tr>\n<tr>\n<td>Abdelghani4</td>\n<td>-1.5554</td>\n<td>-2.8191</td>\n<td>-41.4001</td>\n</tr>\n<tr>\n<td>yuexiliuli26</td>\n<td>-1.6052</td>\n<td>-1.2212</td>\n<td>-1.3027</td>\n</tr>\n<tr>\n<td>Monique14</td>\n<td>-1.6301</td>\n<td>-1.1731</td>\n<td>-0.2715</td>\n</tr>\n<tr>\n<td>Monique11</td>\n<td>-1.7538</td>\n<td>-1.9617</td>\n<td>-4.861</td>\n</tr>\n<tr>\n<td>yuexiliuli12</td>\n<td>-1.7705</td>\n<td>-0.267</td>\n<td>-0.7969</td>\n</tr>\n<tr>\n<td>yuexiliuli15</td>\n<td>-1.7857</td>\n<td>0.0867</td>\n<td>-0.8558</td>\n</tr>\n<tr>\n<td>RonvanBree1</td>\n<td>-1.7915</td>\n<td>-0.9004</td>\n<td>-0.5063</td>\n</tr>\n<tr>\n<td>Johannes3</td>\n<td>-1.7948</td>\n<td>-1.1841</td>\n<td>-1.0573</td>\n</tr>\n<tr>\n<td>yuexiliuli9</td>\n<td>-1.9883</td>\n<td>-0.3159</td>\n<td>-23.2813</td>\n</tr>\n<tr>\n<td>Jiang5</td>\n<td>-2.0099</td>\n<td>-4.4471</td>\n<td>-2.472</td>\n</tr>\n<tr>\n<td>Johannes4</td>\n<td>-2.1137</td>\n<td>-2.905</td>\n<td>-2.8315</td>\n</tr>\n<tr>\n<td>Monique13</td>\n<td>-2.3288</td>\n<td>-1.327</td>\n<td>-7.2944</td>\n</tr>\n<tr>\n<td>Jiang3</td>\n<td>-2.4754</td>\n<td>-3.513</td>\n<td>-4.6779</td>\n</tr>\n<tr>\n<td>Monique9</td>\n<td>-2.9386</td>\n<td>-1.2431</td>\n<td>-8.4138</td>\n</tr>\n<tr>\n<td>yuexiliuli2</td>\n<td>-3.0455</td>\n<td>-0.7044</td>\n<td>-17.2027</td>\n</tr>\n<tr>\n<td>Thomas1</td>\n<td>-3.2773</td>\n<td>-1.8043</td>\n<td>-15.2508</td>\n</tr>\n<tr>\n<td>Abdelghani3</td>\n<td>-5.2269</td>\n<td>-8.2214</td>\n<td>-23.0564</td>\n</tr>\n<tr>\n<td>Abdelghani2</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>Abdelghani1</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>Lilybelle1</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>yuexiliuli1</td>\n<td>-5.4367</td>\n<td>-0.8075</td>\n<td>-13.9148</td>\n</tr>\n<tr>\n<td>yuexiliuli4</td>\n<td>-5.688</td>\n<td>-5.9317</td>\n<td>-22.5848</td>\n</tr>\n<tr>\n<td>yuexiliuli6</td>\n<td>-5.8034</td>\n<td>-2.4714</td>\n<td>-22.614</td>\n</tr>\n<tr>\n<td>yuexiliuli8</td>\n<td>-5.9358</td>\n<td>-5.5684</td>\n<td>-23.2787</td>\n</tr>\n<tr>\n<td>K14</td>\n<td>-6.0147</td>\n<td>-3.59</td>\n<td>-56.1686</td>\n</tr>\n<tr>\n<td>yuexiliuli5</td>\n<td>-6.1589</td>\n<td>-11.1909</td>\n<td>-22.5821</td>\n</tr>\n<tr>\n<td>yuexiliuli3</td>\n<td>-6.2546</td>\n<td>-6.5211</td>\n<td>-23.1889</td>\n</tr>\n<tr>\n<td>yuexiliuli7</td>\n<td>-7.5776</td>\n<td>-2.7282</td>\n<td>-22.3713</td>\n</tr>\n<tr>\n<td>K3</td>\n<td>-8.2054</td>\n<td>-27.6892</td>\n<td>-28.0561</td>\n</tr>\n<tr>\n<td>yuexiliuli11</td>\n<td>-9.1963</td>\n<td>-12.9769</td>\n<td>-46.3724</td>\n</tr>\n<tr>\n<td>yuexiliuli10</td>\n<td>-14.9517</td>\n<td>-5.8695</td>\n<td>-68.1515</td>\n</tr>\n<tr>\n<td>yuexiliuli24</td>\n<td>-17.9077</td>\n<td>-24.8179</td>\n<td>-50.9584</td>\n</tr>\n<tr>\n<td>yuexiliuli23</td>\n<td>-17.9081</td>\n<td>-24.356</td>\n<td>-51.5917</td>\n</tr>\n<tr>\n<td>Jiang4</td>\n<td>-18.9558</td>\n<td>-4.4471</td>\n<td>-33.8965</td>\n</tr>\n<tr>\n<td>K4</td>\n<td>-24.7473</td>\n<td>-0.2668</td>\n<td>-55.0121</td>\n</tr>\n<tr>\n<td>yuexiliuli13</td>\n<td>-26.1638</td>\n<td>-14.6006</td>\n<td>-0.0259</td>\n</tr>\n<tr>\n<td>K7</td>\n<td>-4786.0087</td>\n<td>-37598.0004</td>\n<td>-12626.6688</td>\n</tr>\n<tr>\n<td>K12</td>\n<td>-21135.8054</td>\n<td>-16435.3889</td>\n<td>-1359.258</td>\n</tr>\n</tbody>\n</table>",
  "messages": [
    {
      "id": 2935664,
      "postDate": "2024-07-25T13:36:37.623Z",
      "content": "<p><strong>There was an error in the code producing the leaderboard previously! Thanks to Monique for spotting this. The names of the participant were correct, but the submission numbers were not.</strong></p>\n<p>We're not only looking for the best performance in terms of RMSE, but also in terms of how well the models can capture the variability of annual production in breadbasket regions (Iowa for maize, Germany for wheat). Furthermore, as we find that often models overfit spatially but don't manage to get the temporal variability at each gridcell, we also measure the median R2 over all gridcells.</p>\n<p>Starting this week, we plan to calculate the scores on these metrics for the validation years (2020-2050) and share the results at ~weekly intervals, so you can see how well your models are performing.</p>\n<p>The number next to your first name or initial indicates which of your submissions this represents - 1 would be the first you submitted, etc. Bold denotes the top three entries for that particular metric.</p>\n<p>Should we consider other metrics as well? Interested in your thoughts!</p>\n<p><strong>Don't forget - to enter the competition it's compulsory to share your code. Please make your notebooks public or contact us to share!</strong></p>\n<table>\n<thead>\n<tr>\n<th>**Submission</th>\n<th>Validation Median R2</th>\n<th>Validation Iowa R2</th>\n<th>Validation Germany R2**</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td><strong>Abdelghani32</strong></td>\n<td>0.0984</td>\n<td>0.5723</td>\n<td>0.1124</td>\n</tr>\n<tr>\n<td><strong>Abdelghani34</strong></td>\n<td>0.0983</td>\n<td>0.5676</td>\n<td>0.125</td>\n</tr>\n<tr>\n<td><strong>Abdelghani33</strong></td>\n<td>0.0958</td>\n<td>0.561</td>\n<td>0.1342</td>\n</tr>\n<tr>\n<td><strong>Monique22</strong></td>\n<td>0.0795</td>\n<td>0.5541</td>\n<td>0.136</td>\n</tr>\n<tr>\n<td><strong>Abdelghani31</strong></td>\n<td>0.075</td>\n<td>0.5738</td>\n<td>0.1084</td>\n</tr>\n<tr>\n<td>Abdelghani28</td>\n<td>0.0744</td>\n<td>0.5737</td>\n<td>0.1032</td>\n</tr>\n<tr>\n<td>Abdelghani30</td>\n<td>0.0703</td>\n<td>0.5717</td>\n<td>0.0977</td>\n</tr>\n<tr>\n<td>Abdelghani29</td>\n<td>0.0702</td>\n<td>0.5721</td>\n<td>0.1133</td>\n</tr>\n<tr>\n<td>Monique18</td>\n<td>0.0532</td>\n<td>0.5629</td>\n<td>0.1219</td>\n</tr>\n<tr>\n<td>Abdelghani27</td>\n<td>0.051</td>\n<td>0.617</td>\n<td>0.115</td>\n</tr>\n<tr>\n<td>Abdelghani24</td>\n<td>0.043</td>\n<td>0.5921</td>\n<td>0.1183</td>\n</tr>\n<tr>\n<td>Abdelghani25</td>\n<td>0.0392</td>\n<td>0.6169</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Abdelghani23</td>\n<td>0.0351</td>\n<td>0.5755</td>\n<td>0.1082</td>\n</tr>\n<tr>\n<td>Abdelghani26</td>\n<td>0.0326</td>\n<td>0.5643</td>\n<td>0.0935</td>\n</tr>\n<tr>\n<td>Abdelghani22</td>\n<td>0.005</td>\n<td>0.5333</td>\n<td>0.0645</td>\n</tr>\n<tr>\n<td>Abdelghani16</td>\n<td>0.0027</td>\n<td>0.5814</td>\n<td>0.1255</td>\n</tr>\n<tr>\n<td>Abdelghani15</td>\n<td>-0.0019</td>\n<td>0.576</td>\n<td>0.1159</td>\n</tr>\n<tr>\n<td>Johannes22</td>\n<td>-0.0066</td>\n<td>-0.1648</td>\n<td>0.1255</td>\n</tr>\n<tr>\n<td>Monique19</td>\n<td>-0.0067</td>\n<td>0.1688</td>\n<td>0.1374</td>\n</tr>\n<tr>\n<td>Johannes16</td>\n<td>-0.0123</td>\n<td>-0.6302</td>\n<td>-0.0297</td>\n</tr>\n<tr>\n<td>Abdelghani13</td>\n<td>-0.0134</td>\n<td>0.5699</td>\n<td>0.1058</td>\n</tr>\n<tr>\n<td>Johannes12</td>\n<td>-0.0168</td>\n<td>-0.2099</td>\n<td>-0.0358</td>\n</tr>\n<tr>\n<td>Johannes19</td>\n<td>-0.0176</td>\n<td>0.0521</td>\n<td>0.0434</td>\n</tr>\n<tr>\n<td>Johannes17</td>\n<td>-0.0185</td>\n<td>-0.1494</td>\n<td>-0.0392</td>\n</tr>\n<tr>\n<td>Abdelghani17</td>\n<td>-0.0199</td>\n<td>0.5984</td>\n<td>0.1719</td>\n</tr>\n<tr>\n<td>Johannes21</td>\n<td>-0.0214</td>\n<td>-0.6362</td>\n<td>-0.0465</td>\n</tr>\n<tr>\n<td>Abdelghani14</td>\n<td>-0.0239</td>\n<td>0.5631</td>\n<td>0.0951</td>\n</tr>\n<tr>\n<td>Johannes18</td>\n<td>-0.0291</td>\n<td>-0.8114</td>\n<td>0.117</td>\n</tr>\n<tr>\n<td>Johannes20</td>\n<td>-0.0359</td>\n<td>-0.2832</td>\n<td>-0.0131</td>\n</tr>\n<tr>\n<td>Abdelghani19</td>\n<td>-0.0387</td>\n<td>0.5556</td>\n<td>0.0839</td>\n</tr>\n<tr>\n<td>Abdelghani12</td>\n<td>-0.0387</td>\n<td>0.5556</td>\n<td>0.0839</td>\n</tr>\n<tr>\n<td>Abdelghani18</td>\n<td>-0.0413</td>\n<td>0.4869</td>\n<td>0.0855</td>\n</tr>\n<tr>\n<td>Johannes15</td>\n<td>-0.0418</td>\n<td>-0.345</td>\n<td>0.0767</td>\n</tr>\n<tr>\n<td>Johannes14</td>\n<td>-0.0448</td>\n<td>-0.6308</td>\n<td>0.08</td>\n</tr>\n<tr>\n<td>Abdelghani20</td>\n<td>-0.0693</td>\n<td>0.4633</td>\n<td>0.064</td>\n</tr>\n<tr>\n<td>Abdelghani21</td>\n<td>-0.1319</td>\n<td>0.4343</td>\n<td>0.0658</td>\n</tr>\n<tr>\n<td>Monique17</td>\n<td>-0.1639</td>\n<td><strong>0.7599</strong></td>\n<td><strong>0.1983</strong></td>\n</tr>\n<tr>\n<td>K2</td>\n<td>-0.1658</td>\n<td>0.4537</td>\n<td><strong>0.235</strong></td>\n</tr>\n<tr>\n<td>K1</td>\n<td>-0.1658</td>\n<td>0.4537</td>\n<td><strong>0.235</strong></td>\n</tr>\n<tr>\n<td>Divya1</td>\n<td>-0.1808</td>\n<td>0.4543</td>\n<td>0.1801</td>\n</tr>\n<tr>\n<td>Johannes13</td>\n<td>-0.1906</td>\n<td>-0.717</td>\n<td>0.01</td>\n</tr>\n<tr>\n<td>Abdelghani5</td>\n<td>-0.2021</td>\n<td>-0.5034</td>\n<td>-0.0258</td>\n</tr>\n<tr>\n<td>Monique20</td>\n<td>-0.2307</td>\n<td>-0.7257</td>\n<td>-0.0181</td>\n</tr>\n<tr>\n<td>Divya2</td>\n<td>-0.2443</td>\n<td>0.2476</td>\n<td>0.1434</td>\n</tr>\n<tr>\n<td>Abdelghani8</td>\n<td>-0.2712</td>\n<td>-0.5237</td>\n<td>-0.0151</td>\n</tr>\n<tr>\n<td>Abdelghani7</td>\n<td>-0.2722</td>\n<td>-0.5479</td>\n<td>-0.2447</td>\n</tr>\n<tr>\n<td>Lilybelle4</td>\n<td>-0.3237</td>\n<td>0.4267</td>\n<td>0.0434</td>\n</tr>\n<tr>\n<td>Johannes10</td>\n<td>-0.3239</td>\n<td>0.2614</td>\n<td>-0.3375</td>\n</tr>\n<tr>\n<td>Monique12</td>\n<td>-0.3302</td>\n<td>0.5687</td>\n<td><strong>0.2064</strong></td>\n</tr>\n<tr>\n<td>Monique16</td>\n<td>-0.3341</td>\n<td><strong>0.7025</strong></td>\n<td>0.1672</td>\n</tr>\n<tr>\n<td>Monique21</td>\n<td>-0.3373</td>\n<td>-2.794</td>\n<td>-0.0167</td>\n</tr>\n<tr>\n<td>Abdelghani10</td>\n<td>-0.3422</td>\n<td>0.5622</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Abdelghani11</td>\n<td>-0.3422</td>\n<td>0.5622</td>\n<td>0.1389</td>\n</tr>\n<tr>\n<td>Lilybelle2</td>\n<td>-0.3586</td>\n<td>-2.8099</td>\n<td>-0.0279</td>\n</tr>\n<tr>\n<td>Monique10</td>\n<td>-0.3655</td>\n<td>0.6148</td>\n<td><strong>0.2401</strong></td>\n</tr>\n<tr>\n<td>Johannes11</td>\n<td>-0.3713</td>\n<td>-2.3285</td>\n<td>0.0249</td>\n</tr>\n<tr>\n<td>Jonathan4</td>\n<td>-0.457</td>\n<td>-3.7363</td>\n<td>0.0177</td>\n</tr>\n<tr>\n<td>Jonathan1</td>\n<td>-0.4632</td>\n<td>-3.6195</td>\n<td>0.0592</td>\n</tr>\n<tr>\n<td>Jonathan2</td>\n<td>-0.4632</td>\n<td>-3.6195</td>\n<td>0.0592</td>\n</tr>\n<tr>\n<td>Johannes9</td>\n<td>-0.4742</td>\n<td>-0.0028</td>\n<td><strong>0.2706</strong></td>\n</tr>\n<tr>\n<td>Jonathan3</td>\n<td>-0.4874</td>\n<td>-3.6378</td>\n<td>0.0373</td>\n</tr>\n<tr>\n<td>Monique1</td>\n<td>-0.5523</td>\n<td><strong>0.6535</strong></td>\n<td>0.1653</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava4</td>\n<td>-0.5528</td>\n<td>0.6285</td>\n<td>0.1671</td>\n</tr>\n<tr>\n<td>Monique8</td>\n<td>-0.5618</td>\n<td>0.513</td>\n<td>-0.0133</td>\n</tr>\n<tr>\n<td>Monique7</td>\n<td>-0.5618</td>\n<td>0.513</td>\n<td>-0.0133</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava5</td>\n<td>-0.5768</td>\n<td><strong>0.7597</strong></td>\n<td>0.1903</td>\n</tr>\n<tr>\n<td>Monique6</td>\n<td>-0.5799</td>\n<td><strong>0.6531</strong></td>\n<td>0.0391</td>\n</tr>\n<tr>\n<td>Johannes8</td>\n<td>-0.6036</td>\n<td>-3.5369</td>\n<td>-0.042</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava3</td>\n<td>-0.6128</td>\n<td>0.4357</td>\n<td>0.0929</td>\n</tr>\n<tr>\n<td>Johannes6</td>\n<td>-0.6176</td>\n<td>0.3287</td>\n<td>-0.8237</td>\n</tr>\n<tr>\n<td>Johannes5</td>\n<td>-0.6176</td>\n<td>0.3287</td>\n<td>-0.8237</td>\n</tr>\n<tr>\n<td>Abdelghani6</td>\n<td>-0.6225</td>\n<td>-0.8669</td>\n<td>-0.3743</td>\n</tr>\n<tr>\n<td>Lilybelle3</td>\n<td>-0.6497</td>\n<td>0.3706</td>\n<td>0.0267</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava1</td>\n<td>-0.6527</td>\n<td>0.4069</td>\n<td>0.0403</td>\n</tr>\n<tr>\n<td>AmittKumarrSrivastava2</td>\n<td>-0.6527</td>\n<td>0.4069</td>\n<td>0.0403</td>\n</tr>\n<tr>\n<td>Monique4</td>\n<td>-0.6833</td>\n<td>-0.0321</td>\n<td>-0.033</td>\n</tr>\n<tr>\n<td>Johannes2</td>\n<td>-0.6975</td>\n<td>-0.6625</td>\n<td>-2.1401</td>\n</tr>\n<tr>\n<td>JasonTarzan4</td>\n<td>-0.723</td>\n<td>0.148</td>\n<td>-0.008</td>\n</tr>\n<tr>\n<td>K6</td>\n<td>-0.7393</td>\n<td>0.453</td>\n<td>-12.0148</td>\n</tr>\n<tr>\n<td>Johannes1</td>\n<td>-0.7699</td>\n<td>-0.5199</td>\n<td>-1.4573</td>\n</tr>\n<tr>\n<td>Abdelghani9</td>\n<td>-0.7879</td>\n<td>0.003</td>\n<td>-0.069</td>\n</tr>\n<tr>\n<td>JasonTarzan3</td>\n<td>-0.7972</td>\n<td>0.1843</td>\n<td>0.1715</td>\n</tr>\n<tr>\n<td>JasonTarzan5</td>\n<td>-0.8373</td>\n<td>0.4139</td>\n<td>-0.0457</td>\n</tr>\n<tr>\n<td>K13</td>\n<td>-0.8707</td>\n<td>0.4459</td>\n<td>-19.0715</td>\n</tr>\n<tr>\n<td>K5</td>\n<td>-0.9618</td>\n<td>0.4275</td>\n<td>-15.2131</td>\n</tr>\n<tr>\n<td>Monique5</td>\n<td>-1.046</td>\n<td>-0.0292</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Jiang1</td>\n<td>-1.0538</td>\n<td>0.2185</td>\n<td>-0.4389</td>\n</tr>\n<tr>\n<td>Jiang2</td>\n<td>-1.0538</td>\n<td>0.2185</td>\n<td>-0.4389</td>\n</tr>\n<tr>\n<td>yuexiliuli18</td>\n<td>-1.1213</td>\n<td>-0.0236</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Monique15</td>\n<td>-1.1663</td>\n<td>-2.2257</td>\n<td>-6.7435</td>\n</tr>\n<tr>\n<td>K9</td>\n<td>-1.1718</td>\n<td>-2.6885</td>\n<td>-1.1253</td>\n</tr>\n<tr>\n<td>Johannes7</td>\n<td>-1.1726</td>\n<td>0.454</td>\n<td>-0.4443</td>\n</tr>\n<tr>\n<td>yuexiliuli25</td>\n<td>-1.1951</td>\n<td>-1.4452</td>\n<td>0.0314</td>\n</tr>\n<tr>\n<td>yuexiliuli17</td>\n<td>-1.2294</td>\n<td>-0.3931</td>\n<td>-1.1102</td>\n</tr>\n<tr>\n<td>K10</td>\n<td>-1.232</td>\n<td>-2.4394</td>\n<td>-1.8217</td>\n</tr>\n<tr>\n<td>Jiang6</td>\n<td>-1.2371</td>\n<td>0.5205</td>\n<td>-0.268</td>\n</tr>\n<tr>\n<td>JasonTarzan1</td>\n<td>-1.2402</td>\n<td>0.294</td>\n<td>-0.1699</td>\n</tr>\n<tr>\n<td>yuexiliuli16</td>\n<td>-1.2554</td>\n<td>0.1683</td>\n<td>-1.4837</td>\n</tr>\n<tr>\n<td>yuexiliuli20</td>\n<td>-1.296</td>\n<td>-0.5994</td>\n<td>-0.95</td>\n</tr>\n<tr>\n<td>K11</td>\n<td>-1.2995</td>\n<td>-5.5441</td>\n<td>-1.984</td>\n</tr>\n<tr>\n<td>yuexiliuli19</td>\n<td>-1.3151</td>\n<td>0.1852</td>\n<td>0.1641</td>\n</tr>\n<tr>\n<td>JasonTarzan2</td>\n<td>-1.3462</td>\n<td>-1.1281</td>\n<td>-0.6062</td>\n</tr>\n<tr>\n<td>Jiang7</td>\n<td>-1.4319</td>\n<td>-3.4144</td>\n<td>-0.122</td>\n</tr>\n<tr>\n<td>K8</td>\n<td>-1.4378</td>\n<td>-3.2419</td>\n<td>-1.2659</td>\n</tr>\n<tr>\n<td>RonvanBree2</td>\n<td>-1.4472</td>\n<td>0.4056</td>\n<td>-0.5598</td>\n</tr>\n<tr>\n<td>yuexiliuli21</td>\n<td>-1.4641</td>\n<td>-11.0763</td>\n<td>-0.291</td>\n</tr>\n<tr>\n<td>Monique3</td>\n<td>-1.5162</td>\n<td>-0.0122</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>Monique2</td>\n<td>-1.5162</td>\n<td>-0.0122</td>\n<td>-0.2779</td>\n</tr>\n<tr>\n<td>yuexiliuli22</td>\n<td>-1.5375</td>\n<td>-7.5931</td>\n<td>-2.0214</td>\n</tr>\n<tr>\n<td>yuexiliuli14</td>\n<td>-1.5391</td>\n<td>-0.3425</td>\n<td>-1.0263</td>\n</tr>\n<tr>\n<td>Abdelghani4</td>\n<td>-1.5554</td>\n<td>-2.8191</td>\n<td>-41.4001</td>\n</tr>\n<tr>\n<td>yuexiliuli26</td>\n<td>-1.6052</td>\n<td>-1.2212</td>\n<td>-1.3027</td>\n</tr>\n<tr>\n<td>Monique14</td>\n<td>-1.6301</td>\n<td>-1.1731</td>\n<td>-0.2715</td>\n</tr>\n<tr>\n<td>Monique11</td>\n<td>-1.7538</td>\n<td>-1.9617</td>\n<td>-4.861</td>\n</tr>\n<tr>\n<td>yuexiliuli12</td>\n<td>-1.7705</td>\n<td>-0.267</td>\n<td>-0.7969</td>\n</tr>\n<tr>\n<td>yuexiliuli15</td>\n<td>-1.7857</td>\n<td>0.0867</td>\n<td>-0.8558</td>\n</tr>\n<tr>\n<td>RonvanBree1</td>\n<td>-1.7915</td>\n<td>-0.9004</td>\n<td>-0.5063</td>\n</tr>\n<tr>\n<td>Johannes3</td>\n<td>-1.7948</td>\n<td>-1.1841</td>\n<td>-1.0573</td>\n</tr>\n<tr>\n<td>yuexiliuli9</td>\n<td>-1.9883</td>\n<td>-0.3159</td>\n<td>-23.2813</td>\n</tr>\n<tr>\n<td>Jiang5</td>\n<td>-2.0099</td>\n<td>-4.4471</td>\n<td>-2.472</td>\n</tr>\n<tr>\n<td>Johannes4</td>\n<td>-2.1137</td>\n<td>-2.905</td>\n<td>-2.8315</td>\n</tr>\n<tr>\n<td>Monique13</td>\n<td>-2.3288</td>\n<td>-1.327</td>\n<td>-7.2944</td>\n</tr>\n<tr>\n<td>Jiang3</td>\n<td>-2.4754</td>\n<td>-3.513</td>\n<td>-4.6779</td>\n</tr>\n<tr>\n<td>Monique9</td>\n<td>-2.9386</td>\n<td>-1.2431</td>\n<td>-8.4138</td>\n</tr>\n<tr>\n<td>yuexiliuli2</td>\n<td>-3.0455</td>\n<td>-0.7044</td>\n<td>-17.2027</td>\n</tr>\n<tr>\n<td>Thomas1</td>\n<td>-3.2773</td>\n<td>-1.8043</td>\n<td>-15.2508</td>\n</tr>\n<tr>\n<td>Abdelghani3</td>\n<td>-5.2269</td>\n<td>-8.2214</td>\n<td>-23.0564</td>\n</tr>\n<tr>\n<td>Abdelghani2</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>Abdelghani1</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>Lilybelle1</td>\n<td>-5.3518</td>\n<td>-8.1132</td>\n<td>-22.5979</td>\n</tr>\n<tr>\n<td>yuexiliuli1</td>\n<td>-5.4367</td>\n<td>-0.8075</td>\n<td>-13.9148</td>\n</tr>\n<tr>\n<td>yuexiliuli4</td>\n<td>-5.688</td>\n<td>-5.9317</td>\n<td>-22.5848</td>\n</tr>\n<tr>\n<td>yuexiliuli6</td>\n<td>-5.8034</td>\n<td>-2.4714</td>\n<td>-22.614</td>\n</tr>\n<tr>\n<td>yuexiliuli8</td>\n<td>-5.9358</td>\n<td>-5.5684</td>\n<td>-23.2787</td>\n</tr>\n<tr>\n<td>K14</td>\n<td>-6.0147</td>\n<td>-3.59</td>\n<td>-56.1686</td>\n</tr>\n<tr>\n<td>yuexiliuli5</td>\n<td>-6.1589</td>\n<td>-11.1909</td>\n<td>-22.5821</td>\n</tr>\n<tr>\n<td>yuexiliuli3</td>\n<td>-6.2546</td>\n<td>-6.5211</td>\n<td>-23.1889</td>\n</tr>\n<tr>\n<td>yuexiliuli7</td>\n<td>-7.5776</td>\n<td>-2.7282</td>\n<td>-22.3713</td>\n</tr>\n<tr>\n<td>K3</td>\n<td>-8.2054</td>\n<td>-27.6892</td>\n<td>-28.0561</td>\n</tr>\n<tr>\n<td>yuexiliuli11</td>\n<td>-9.1963</td>\n<td>-12.9769</td>\n<td>-46.3724</td>\n</tr>\n<tr>\n<td>yuexiliuli10</td>\n<td>-14.9517</td>\n<td>-5.8695</td>\n<td>-68.1515</td>\n</tr>\n<tr>\n<td>yuexiliuli24</td>\n<td>-17.9077</td>\n<td>-24.8179</td>\n<td>-50.9584</td>\n</tr>\n<tr>\n<td>yuexiliuli23</td>\n<td>-17.9081</td>\n<td>-24.356</td>\n<td>-51.5917</td>\n</tr>\n<tr>\n<td>Jiang4</td>\n<td>-18.9558</td>\n<td>-4.4471</td>\n<td>-33.8965</td>\n</tr>\n<tr>\n<td>K4</td>\n<td>-24.7473</td>\n<td>-0.2668</td>\n<td>-55.0121</td>\n</tr>\n<tr>\n<td>yuexiliuli13</td>\n<td>-26.1638</td>\n<td>-14.6006</td>\n<td>-0.0259</td>\n</tr>\n<tr>\n<td>K7</td>\n<td>-4786.0087</td>\n<td>-37598.0004</td>\n<td>-12626.6688</td>\n</tr>\n<tr>\n<td>K12</td>\n<td>-21135.8054</td>\n<td>-16435.3889</td>\n<td>-1359.258</td>\n</tr>\n</tbody>\n</table>",
      "rawMarkdown": "**There was an error in the code producing the leaderboard previously! Thanks to Monique for spotting this. The names of the participant were correct, but the submission numbers were not.**\n\nWe're not only looking for the best performance in terms of RMSE, but also in terms of how well the models can capture the variability of annual production in breadbasket regions (Iowa for maize, Germany for wheat). Furthermore, as we find that often models overfit spatially but don't manage to get the temporal variability at each gridcell, we also measure the median R2 over all gridcells.\n\nStarting this week, we plan to calculate the scores on these metrics for the validation years (2020-2050) and share the results at ~weekly intervals, so you can see how well your models are performing.\n\nThe number next to your first name or initial indicates which of your submissions this represents - 1 would be the first you submitted, etc. Bold denotes the top three entries for that particular metric.\n\nShould we consider other metrics as well? Interested in your thoughts!\n\n**Don't forget - to enter the competition it's compulsory to share your code. Please make your notebooks public or contact us to share!**\n\n**Submission|Validation Median R2|Validation Iowa R2|Validation Germany R2**\n---|---|---|---\n**Abdelghani32**|0.0984|0.5723|0.1124\n**Abdelghani34**|0.0983|0.5676|0.125\n**Abdelghani33**|0.0958|0.561|0.1342\n**Monique22**|0.0795|0.5541|0.136\n**Abdelghani31**|0.075|0.5738|0.1084\nAbdelghani28|0.0744|0.5737|0.1032\nAbdelghani30|0.0703|0.5717|0.0977\nAbdelghani29|0.0702|0.5721|0.1133\nMonique18|0.0532|0.5629|0.1219\nAbdelghani27|0.051|0.617|0.115\nAbdelghani24|0.043|0.5921|0.1183\nAbdelghani25|0.0392|0.6169|0.1389\nAbdelghani23|0.0351|0.5755|0.1082\nAbdelghani26|0.0326|0.5643|0.0935\nAbdelghani22|0.005|0.5333|0.0645\nAbdelghani16|0.0027|0.5814|0.1255\nAbdelghani15|-0.0019|0.576|0.1159\nJohannes22|-0.0066|-0.1648|0.1255\nMonique19|-0.0067|0.1688|0.1374\nJohannes16|-0.0123|-0.6302|-0.0297\nAbdelghani13|-0.0134|0.5699|0.1058\nJohannes12|-0.0168|-0.2099|-0.0358\nJohannes19|-0.0176|0.0521|0.0434\nJohannes17|-0.0185|-0.1494|-0.0392\nAbdelghani17|-0.0199|0.5984|0.1719\nJohannes21|-0.0214|-0.6362|-0.0465\nAbdelghani14|-0.0239|0.5631|0.0951\nJohannes18|-0.0291|-0.8114|0.117\nJohannes20|-0.0359|-0.2832|-0.0131\nAbdelghani19|-0.0387|0.5556|0.0839\nAbdelghani12|-0.0387|0.5556|0.0839\nAbdelghani18|-0.0413|0.4869|0.0855\nJohannes15|-0.0418|-0.345|0.0767\nJohannes14|-0.0448|-0.6308|0.08\nAbdelghani20|-0.0693|0.4633|0.064\nAbdelghani21|-0.1319|0.4343|0.0658\nMonique17|-0.1639|**0.7599**|**0.1983**\nK2|-0.1658|0.4537|**0.235**\nK1|-0.1658|0.4537|**0.235**\nDivya1|-0.1808|0.4543|0.1801\nJohannes13|-0.1906|-0.717|0.01\nAbdelghani5|-0.2021|-0.5034|-0.0258\nMonique20|-0.2307|-0.7257|-0.0181\nDivya2|-0.2443|0.2476|0.1434\nAbdelghani8|-0.2712|-0.5237|-0.0151\nAbdelghani7|-0.2722|-0.5479|-0.2447\nLilybelle4|-0.3237|0.4267|0.0434\nJohannes10|-0.3239|0.2614|-0.3375\nMonique12|-0.3302|0.5687|**0.2064**\nMonique16|-0.3341|**0.7025**|0.1672\nMonique21|-0.3373|-2.794|-0.0167\nAbdelghani10|-0.3422|0.5622|0.1389\nAbdelghani11|-0.3422|0.5622|0.1389\nLilybelle2|-0.3586|-2.8099|-0.0279\nMonique10|-0.3655|0.6148|**0.2401**\nJohannes11|-0.3713|-2.3285|0.0249\nJonathan4|-0.457|-3.7363|0.0177\nJonathan1|-0.4632|-3.6195|0.0592\nJonathan2|-0.4632|-3.6195|0.0592\nJohannes9|-0.4742|-0.0028|**0.2706**\nJonathan3|-0.4874|-3.6378|0.0373\nMonique1|-0.5523|**0.6535**|0.1653\nAmittKumarrSrivastava4|-0.5528|0.6285|0.1671\nMonique8|-0.5618|0.513|-0.0133\nMonique7|-0.5618|0.513|-0.0133\nAmittKumarrSrivastava5|-0.5768|**0.7597**|0.1903\nMonique6|-0.5799|**0.6531**|0.0391\nJohannes8|-0.6036|-3.5369|-0.042\nAmittKumarrSrivastava3|-0.6128|0.4357|0.0929\nJohannes6|-0.6176|0.3287|-0.8237\nJohannes5|-0.6176|0.3287|-0.8237\nAbdelghani6|-0.6225|-0.8669|-0.3743\nLilybelle3|-0.6497|0.3706|0.0267\nAmittKumarrSrivastava1|-0.6527|0.4069|0.0403\nAmittKumarrSrivastava2|-0.6527|0.4069|0.0403\nMonique4|-0.6833|-0.0321|-0.033\nJohannes2|-0.6975|-0.6625|-2.1401\nJasonTarzan4|-0.723|0.148|-0.008\nK6|-0.7393|0.453|-12.0148\nJohannes1|-0.7699|-0.5199|-1.4573\nAbdelghani9|-0.7879|0.003|-0.069\nJasonTarzan3|-0.7972|0.1843|0.1715\nJasonTarzan5|-0.8373|0.4139|-0.0457\nK13|-0.8707|0.4459|-19.0715\nK5|-0.9618|0.4275|-15.2131\nMonique5|-1.046|-0.0292|-0.2779\nJiang1|-1.0538|0.2185|-0.4389\nJiang2|-1.0538|0.2185|-0.4389\nyuexiliuli18|-1.1213|-0.0236|-0.2779\nMonique15|-1.1663|-2.2257|-6.7435\nK9|-1.1718|-2.6885|-1.1253\nJohannes7|-1.1726|0.454|-0.4443\nyuexiliuli25|-1.1951|-1.4452|0.0314\nyuexiliuli17|-1.2294|-0.3931|-1.1102\nK10|-1.232|-2.4394|-1.8217\nJiang6|-1.2371|0.5205|-0.268\nJasonTarzan1|-1.2402|0.294|-0.1699\nyuexiliuli16|-1.2554|0.1683|-1.4837\nyuexiliuli20|-1.296|-0.5994|-0.95\nK11|-1.2995|-5.5441|-1.984\nyuexiliuli19|-1.3151|0.1852|0.1641\nJasonTarzan2|-1.3462|-1.1281|-0.6062\nJiang7|-1.4319|-3.4144|-0.122\nK8|-1.4378|-3.2419|-1.2659\nRonvanBree2|-1.4472|0.4056|-0.5598\nyuexiliuli21|-1.4641|-11.0763|-0.291\nMonique3|-1.5162|-0.0122|-0.2779\nMonique2|-1.5162|-0.0122|-0.2779\nyuexiliuli22|-1.5375|-7.5931|-2.0214\nyuexiliuli14|-1.5391|-0.3425|-1.0263\nAbdelghani4|-1.5554|-2.8191|-41.4001\nyuexiliuli26|-1.6052|-1.2212|-1.3027\nMonique14|-1.6301|-1.1731|-0.2715\nMonique11|-1.7538|-1.9617|-4.861\nyuexiliuli12|-1.7705|-0.267|-0.7969\nyuexiliuli15|-1.7857|0.0867|-0.8558\nRonvanBree1|-1.7915|-0.9004|-0.5063\nJohannes3|-1.7948|-1.1841|-1.0573\nyuexiliuli9|-1.9883|-0.3159|-23.2813\nJiang5|-2.0099|-4.4471|-2.472\nJohannes4|-2.1137|-2.905|-2.8315\nMonique13|-2.3288|-1.327|-7.2944\nJiang3|-2.4754|-3.513|-4.6779\nMonique9|-2.9386|-1.2431|-8.4138\nyuexiliuli2|-3.0455|-0.7044|-17.2027\nThomas1|-3.2773|-1.8043|-15.2508\nAbdelghani3|-5.2269|-8.2214|-23.0564\nAbdelghani2|-5.3518|-8.1132|-22.5979\nAbdelghani1|-5.3518|-8.1132|-22.5979\nLilybelle1|-5.3518|-8.1132|-22.5979\nyuexiliuli1|-5.4367|-0.8075|-13.9148\nyuexiliuli4|-5.688|-5.9317|-22.5848\nyuexiliuli6|-5.8034|-2.4714|-22.614\nyuexiliuli8|-5.9358|-5.5684|-23.2787\nK14|-6.0147|-3.59|-56.1686\nyuexiliuli5|-6.1589|-11.1909|-22.5821\nyuexiliuli3|-6.2546|-6.5211|-23.1889\nyuexiliuli7|-7.5776|-2.7282|-22.3713\nK3|-8.2054|-27.6892|-28.0561\nyuexiliuli11|-9.1963|-12.9769|-46.3724\nyuexiliuli10|-14.9517|-5.8695|-68.1515\nyuexiliuli24|-17.9077|-24.8179|-50.9584\nyuexiliuli23|-17.9081|-24.356|-51.5917\nJiang4|-18.9558|-4.4471|-33.8965\nK4|-24.7473|-0.2668|-55.0121\nyuexiliuli13|-26.1638|-14.6006|-0.0259\nK7|-4786.0087|-37598.0004|-12626.6688\nK12|-21135.8054|-16435.3889|-1359.258",
      "votes": 2
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2935664": "**There was an error in the code producing the leaderboard previously! Thanks to Monique for spotting this. The names of the participant were correct, but the submission numbers were not.**\n\nWe're not only looking for the best performance in terms of RMSE, but also in terms of how well the models can capture the variability of annual production in breadbasket regions (Iowa for maize, Germany for wheat). Furthermore, as we find that often models overfit spatially but don't manage to get the temporal variability at each gridcell, we also measure the median R2 over all gridcells.\n\nStarting this week, we plan to calculate the scores on these metrics for the validation years (2020-2050) and share the results at ~weekly intervals, so you can see how well your models are performing.\n\nThe number next to your first name or initial indicates which of your submissions this represents - 1 would be the first you submitted, etc. Bold denotes the top three entries for that particular metric.\n\nShould we consider other metrics as well? Interested in your thoughts!\n\n**Don't forget - to enter the competition it's compulsory to share your code. Please make your notebooks public or contact us to share!**\n\n**Submission|Validation Median R2|Validation Iowa R2|Validation Germany R2**\n---|---|---|---\n**Abdelghani32**|0.0984|0.5723|0.1124\n**Abdelghani34**|0.0983|0.5676|0.125\n**Abdelghani33**|0.0958|0.561|0.1342\n**Monique22**|0.0795|0.5541|0.136\n**Abdelghani31**|0.075|0.5738|0.1084\nAbdelghani28|0.0744|0.5737|0.1032\nAbdelghani30|0.0703|0.5717|0.0977\nAbdelghani29|0.0702|0.5721|0.1133\nMonique18|0.0532|0.5629|0.1219\nAbdelghani27|0.051|0.617|0.115\nAbdelghani24|0.043|0.5921|0.1183\nAbdelghani25|0.0392|0.6169|0.1389\nAbdelghani23|0.0351|0.5755|0.1082\nAbdelghani26|0.0326|0.5643|0.0935\nAbdelghani22|0.005|0.5333|0.0645\nAbdelghani16|0.0027|0.5814|0.1255\nAbdelghani15|-0.0019|0.576|0.1159\nJohannes22|-0.0066|-0.1648|0.1255\nMonique19|-0.0067|0.1688|0.1374\nJohannes16|-0.0123|-0.6302|-0.0297\nAbdelghani13|-0.0134|0.5699|0.1058\nJohannes12|-0.0168|-0.2099|-0.0358\nJohannes19|-0.0176|0.0521|0.0434\nJohannes17|-0.0185|-0.1494|-0.0392\nAbdelghani17|-0.0199|0.5984|0.1719\nJohannes21|-0.0214|-0.6362|-0.0465\nAbdelghani14|-0.0239|0.5631|0.0951\nJohannes18|-0.0291|-0.8114|0.117\nJohannes20|-0.0359|-0.2832|-0.0131\nAbdelghani19|-0.0387|0.5556|0.0839\nAbdelghani12|-0.0387|0.5556|0.0839\nAbdelghani18|-0.0413|0.4869|0.0855\nJohannes15|-0.0418|-0.345|0.0767\nJohannes14|-0.0448|-0.6308|0.08\nAbdelghani20|-0.0693|0.4633|0.064\nAbdelghani21|-0.1319|0.4343|0.0658\nMonique17|-0.1639|**0.7599**|**0.1983**\nK2|-0.1658|0.4537|**0.235**\nK1|-0.1658|0.4537|**0.235**\nDivya1|-0.1808|0.4543|0.1801\nJohannes13|-0.1906|-0.717|0.01\nAbdelghani5|-0.2021|-0.5034|-0.0258\nMonique20|-0.2307|-0.7257|-0.0181\nDivya2|-0.2443|0.2476|0.1434\nAbdelghani8|-0.2712|-0.5237|-0.0151\nAbdelghani7|-0.2722|-0.5479|-0.2447\nLilybelle4|-0.3237|0.4267|0.0434\nJohannes10|-0.3239|0.2614|-0.3375\nMonique12|-0.3302|0.5687|**0.2064**\nMonique16|-0.3341|**0.7025**|0.1672\nMonique21|-0.3373|-2.794|-0.0167\nAbdelghani10|-0.3422|0.5622|0.1389\nAbdelghani11|-0.3422|0.5622|0.1389\nLilybelle2|-0.3586|-2.8099|-0.0279\nMonique10|-0.3655|0.6148|**0.2401**\nJohannes11|-0.3713|-2.3285|0.0249\nJonathan4|-0.457|-3.7363|0.0177\nJonathan1|-0.4632|-3.6195|0.0592\nJonathan2|-0.4632|-3.6195|0.0592\nJohannes9|-0.4742|-0.0028|**0.2706**\nJonathan3|-0.4874|-3.6378|0.0373\nMonique1|-0.5523|**0.6535**|0.1653\nAmittKumarrSrivastava4|-0.5528|0.6285|0.1671\nMonique8|-0.5618|0.513|-0.0133\nMonique7|-0.5618|0.513|-0.0133\nAmittKumarrSrivastava5|-0.5768|**0.7597**|0.1903\nMonique6|-0.5799|**0.6531**|0.0391\nJohannes8|-0.6036|-3.5369|-0.042\nAmittKumarrSrivastava3|-0.6128|0.4357|0.0929\nJohannes6|-0.6176|0.3287|-0.8237\nJohannes5|-0.6176|0.3287|-0.8237\nAbdelghani6|-0.6225|-0.8669|-0.3743\nLilybelle3|-0.6497|0.3706|0.0267\nAmittKumarrSrivastava1|-0.6527|0.4069|0.0403\nAmittKumarrSrivastava2|-0.6527|0.4069|0.0403\nMonique4|-0.6833|-0.0321|-0.033\nJohannes2|-0.6975|-0.6625|-2.1401\nJasonTarzan4|-0.723|0.148|-0.008\nK6|-0.7393|0.453|-12.0148\nJohannes1|-0.7699|-0.5199|-1.4573\nAbdelghani9|-0.7879|0.003|-0.069\nJasonTarzan3|-0.7972|0.1843|0.1715\nJasonTarzan5|-0.8373|0.4139|-0.0457\nK13|-0.8707|0.4459|-19.0715\nK5|-0.9618|0.4275|-15.2131\nMonique5|-1.046|-0.0292|-0.2779\nJiang1|-1.0538|0.2185|-0.4389\nJiang2|-1.0538|0.2185|-0.4389\nyuexiliuli18|-1.1213|-0.0236|-0.2779\nMonique15|-1.1663|-2.2257|-6.7435\nK9|-1.1718|-2.6885|-1.1253\nJohannes7|-1.1726|0.454|-0.4443\nyuexiliuli25|-1.1951|-1.4452|0.0314\nyuexiliuli17|-1.2294|-0.3931|-1.1102\nK10|-1.232|-2.4394|-1.8217\nJiang6|-1.2371|0.5205|-0.268\nJasonTarzan1|-1.2402|0.294|-0.1699\nyuexiliuli16|-1.2554|0.1683|-1.4837\nyuexiliuli20|-1.296|-0.5994|-0.95\nK11|-1.2995|-5.5441|-1.984\nyuexiliuli19|-1.3151|0.1852|0.1641\nJasonTarzan2|-1.3462|-1.1281|-0.6062\nJiang7|-1.4319|-3.4144|-0.122\nK8|-1.4378|-3.2419|-1.2659\nRonvanBree2|-1.4472|0.4056|-0.5598\nyuexiliuli21|-1.4641|-11.0763|-0.291\nMonique3|-1.5162|-0.0122|-0.2779\nMonique2|-1.5162|-0.0122|-0.2779\nyuexiliuli22|-1.5375|-7.5931|-2.0214\nyuexiliuli14|-1.5391|-0.3425|-1.0263\nAbdelghani4|-1.5554|-2.8191|-41.4001\nyuexiliuli26|-1.6052|-1.2212|-1.3027\nMonique14|-1.6301|-1.1731|-0.2715\nMonique11|-1.7538|-1.9617|-4.861\nyuexiliuli12|-1.7705|-0.267|-0.7969\nyuexiliuli15|-1.7857|0.0867|-0.8558\nRonvanBree1|-1.7915|-0.9004|-0.5063\nJohannes3|-1.7948|-1.1841|-1.0573\nyuexiliuli9|-1.9883|-0.3159|-23.2813\nJiang5|-2.0099|-4.4471|-2.472\nJohannes4|-2.1137|-2.905|-2.8315\nMonique13|-2.3288|-1.327|-7.2944\nJiang3|-2.4754|-3.513|-4.6779\nMonique9|-2.9386|-1.2431|-8.4138\nyuexiliuli2|-3.0455|-0.7044|-17.2027\nThomas1|-3.2773|-1.8043|-15.2508\nAbdelghani3|-5.2269|-8.2214|-23.0564\nAbdelghani2|-5.3518|-8.1132|-22.5979\nAbdelghani1|-5.3518|-8.1132|-22.5979\nLilybelle1|-5.3518|-8.1132|-22.5979\nyuexiliuli1|-5.4367|-0.8075|-13.9148\nyuexiliuli4|-5.688|-5.9317|-22.5848\nyuexiliuli6|-5.8034|-2.4714|-22.614\nyuexiliuli8|-5.9358|-5.5684|-23.2787\nK14|-6.0147|-3.59|-56.1686\nyuexiliuli5|-6.1589|-11.1909|-22.5821\nyuexiliuli3|-6.2546|-6.5211|-23.1889\nyuexiliuli7|-7.5776|-2.7282|-22.3713\nK3|-8.2054|-27.6892|-28.0561\nyuexiliuli11|-9.1963|-12.9769|-46.3724\nyuexiliuli10|-14.9517|-5.8695|-68.1515\nyuexiliuli24|-17.9077|-24.8179|-50.9584\nyuexiliuli23|-17.9081|-24.356|-51.5917\nJiang4|-18.9558|-4.4471|-33.8965\nK4|-24.7473|-0.2668|-55.0121\nyuexiliuli13|-26.1638|-14.6006|-0.0259\nK7|-4786.0087|-37598.0004|-12626.6688\nK12|-21135.8054|-16435.3889|-1359.258"
  }
}