diff --git a/evaluation/report.R b/evaluation/report.R
index 5d396a94..721856bc 100644
--- a/evaluation/report.R
+++ b/evaluation/report.R
@@ -6,90 +6,54 @@ library(readr)
 library(scoringutils) 
 library(data.table)
 
-# read in the EpiExpert ensemble forecast and EpiNow2 models
-folders <- list.files(here::here("submissions", "human-forecasts"))
-files <- purrr::map(folders, 
-                    .f = function(folder_name) {
-                      files <- list.files(here::here("submissions", "human-forecasts", folder_name))
-                      paste(here::here("submissions", "human-forecasts", folder_name, files))
-                    }) %>%
-  unlist()
-epiexpert_forecasts <- purrr::map_dfr(files, readr::read_csv) %>%
-  dplyr::mutate(board_name = "EpiExpert-ensemble", 
-                submission_date = forecast_date,
-                horizon = as.numeric(gsub("([0-9]+).*$", "\\1", target))) %>%
-  dplyr::filter(grepl("inc", target), 
-                type == "quantile")
-
-data.table::fwrite(epiexpert_forecasts, 
-                   here::here("human-forecasts", "processed-forecast-data", "all-epiexpert-forecasts.csv"))
-
-
+# helper function to read in all past submissions from a model, bind them together
+# to one file and copy them into the crowd forecast app folder 
+# having them in one place allows to easily include other models in the 
+# crowd forecast report. Could in principle also do without copying
+load_and_copy_forecasts <- function(root_dir, 
+                                    out_file_path, 
+                                    new_board_name) {
+  folders <- list.files(root_dir)
+  files <- purrr::map(folders, 
+                      .f = function(folder_name) {
+                        files <- list.files(here::here(root_dir, folder_name))
+                        paste(here::here(root_dir, folder_name, files))
+                      }) %>%
+    unlist()
+  
+  forecasts <- purrr::map_dfr(files, readr::read_csv) %>%
+    dplyr::mutate(board_name = new_board_name, 
+                  submission_date = forecast_date,
+                  horizon = as.numeric(gsub("([0-9]+).*$", "\\1", target))) %>%
+    dplyr::filter(grepl("inc", target), 
+                  type == "quantile")
+  
+  data.table::fwrite(forecasts, out_file_path)
+}
 
+# read in the EpiExpert ensemble forecast and EpiNow2 models
+load_and_copy_forecasts(root_dir = here::here("submissions", "crowd-forecasts"), 
+                        out_file_path = here::here("crowd-forecast", "processed-forecast-data", "all-epiexpert-forecasts.csv"), 
+                        new_board_name = "EpiExpert-ensemble")
 
 # also read all EpiNow2 forecasts, give them a board_name 
-folders <- list.files(here::here("submissions", "rt-forecasts/"))
-files <- purrr::map(folders, 
-                    .f = function(folder_name) {
-                      files <- list.files(here::here("submissions", "rt-forecasts/", folder_name))
-                      paste(here::here("submissions", "rt-forecasts/", folder_name, files))
-                    }) %>%
-  unlist()
-epinow_forecasts <- purrr::map_dfr(files, readr::read_csv) %>%
-  dplyr::mutate(board_name = "EpiNow2", 
-                submission_date = forecast_date,
-                horizon = as.numeric(gsub("([0-9]+).*$", "\\1", target))) %>%
-  dplyr::filter(grepl("inc", target), 
-                type == "quantile")
-
-data.table::fwrite(epinow_forecasts, 
-                   here::here("human-forecasts", "processed-forecast-data", "all-epinow2-forecasts.csv"))
-
-
-
-
+load_and_copy_forecasts(root_dir = here::here("submissions", "rt-forecasts"), 
+                        out_file_path = here::here("crowd-forecast", "processed-forecast-data", "all-epinow2-forecasts.csv"), 
+                        new_board_name = "EpiNow2")
 
 # also read all EpiNow2 secondary forecasts, give them a board_name 
-folders <- list.files(here::here("submissions", "deaths-from-cases/"))
-files <- purrr::map(folders, 
-                    .f = function(folder_name) {
-                      files <- list.files(here::here("submissions", "deaths-from-cases/", folder_name))
-                      paste(here::here("submissions", "deaths-from-cases/", folder_name, files))
-                    }) %>%
-  unlist()
-epinow_forecasts <- purrr::map_dfr(files, readr::read_csv) %>%
-  dplyr::mutate(board_name = "EpiNow2_secondary", 
-                submission_date = forecast_date,
-                horizon = as.numeric(gsub("([0-9]+).*$", "\\1", target))) %>%
-  dplyr::filter(grepl("inc", target), 
-                type == "quantile")
-
-data.table::fwrite(epinow_forecasts, 
-                   here::here("human-forecasts", "processed-forecast-data", "all-epinow2_secondary-forecasts.csv"))
+load_and_copy_forecasts(root_dir = here::here("submissions", "deaths-from-cases"), 
+                        out_file_path = here::here("crowd-forecast", "processed-forecast-data", "all-epinow2_secondary-forecasts.csv"), 
+                        new_board_name = "EpiNow2_secondary")
 
+# also read all EpiNow2 Rt crowd forecasts, give them a board_name 
+load_and_copy_forecasts(root_dir = here::here("submissions", "crowd-rt-forecasts"), 
+                        out_file_path = here::here("crowd-forecast", "processed-forecast-data", "all-crowd-rt-forecasts.csv"), 
+                        new_board_name = "Crowd-Rt-Forecast")
 
 
-# also read all EpiNow2 Rt crowd forecasts, give them a board_name 
-folders <- list.files(here::here("submissions", "crowd-rt-forecasts/"))
-files <- purrr::map(folders, 
-                    .f = function(folder_name) {
-                      files <- list.files(here::here("submissions", "crowd-rt-forecasts/", folder_name))
-                      paste(here::here("submissions", "crowd-rt-forecasts/", folder_name, files))
-                    }) %>%
-  unlist()
-epinow__crowd_forecasts <- purrr::map_dfr(files, readr::read_csv) %>%
-  dplyr::mutate(board_name = "Crowd-Rt-Forecast", 
-                submission_date = forecast_date,
-                horizon = as.numeric(gsub("([0-9]+).*$", "\\1", target))) %>%
-  dplyr::filter(grepl("inc", target), 
-                type == "quantile")
-
-data.table::fwrite(epinow__crowd_forecasts, 
-                   here::here("human-forecasts", "processed-forecast-data", "all-crowd-rt-forecasts.csv"))
-
-
-# load data --------------------------------------------------------------------
-root_dir <- here::here("human-forecasts", "processed-forecast-data")
+# load all data ----------------------------------------------------------------
+root_dir <- here::here("crowd-forecast", "processed-forecast-data")
 file_paths_forecast <- here::here(root_dir, list.files(root_dir))
 
 prediction_data <- purrr::map_dfr(file_paths_forecast, 
@@ -107,7 +71,6 @@ prediction_data <- purrr::map_dfr(file_paths_forecast,
                 location_name %in% c("Germany", "Poland")) %>%
   dplyr::select(location, location_name, forecast_date, quantile, prediction, model, target_end_date, horizon, target, target_type)
 
-
 files <- list.files("data-raw/")
 file_paths <- paste0("data-raw/", files[grepl("weekly-incident", files)])
 names(file_paths) <- c("case", "death")
@@ -128,15 +91,12 @@ The evaluations are also not authorised by the German Forecast Hub team.
 If you have questions or want to give feedback, please create an issue on our 
 [github repository](https://github.com/epiforecasts/covid-german-forecasts).")
 
-
 params <- list(locations = c("Germany", "Poland"),
                forecast_dates = "all",
                horizons = c(1:4),
                target_types = "all",
                intro_text = intro_text)
 
-
-
 scoringutils::render_scoring_report(truth_data = truth_data, 
                                     document_title = "EpiExpert Crowd-Forecasting Performance Board",
                                     params = params,