R/predict_qb.R

In kimjam/dfstoolkit: Functions to clean fantasy sports data and make weekly projections.

#' @title predict_qb
#' @description make predictions for qb
#'
#' @param qb_dflist list of qb dataframes (one ,two, three week based)
#' @param price df of player prices
#'
#' @return returns dataframe of predictions

predict_qb <- function(qb_dflist, price) {

    price$name <- tolower(gsub("'", "", price$name))
    price <- price %>%
        dplyr::filter(
            position == 'QB'
        )

    oneweek <- qb_dflist[['oneweek']] %>% as.data.frame()
    twoweek <- qb_dflist[['twoweek']] %>% as.data.frame()
    threeweek <- qb_dflist[['threeweek']] %>% as.data.frame()

    null <- data.frame(matrix(ncol=4))
    names(null) = c('name', 'team', 'svm', 'ind')
    null <- null[-1, ]

    if (nrow(oneweek) > 0) {
        oneweek_svm <- predict(qb_svm1, newdata = oneweek)

        td <- predict(qb_td1, newdata = oneweek, 'probs')
        int <- predict(qb_int1, newdata = oneweek, 'probs')
        rtd <- predict(qb_rutd1, newdata = oneweek, 'probs')
        oneweek_ind <- (
            predict(qb_yds1, newdata = oneweek) / 25 +
                predict(qb_ruyds1, newdata = oneweek) / 10 +
                (td %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(td) - 1),
                        0:(ncol(td) - 1)
                    ),
                    nrow = ifelse(is.null(ncol(td)),
                                  length(td),
                                  ncol(td)
                    )
                )) * 4 -
                (int %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(int) - 1),
                        0:(ncol(int) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(td)),
                        length(int),
                        ncol(int)
                    )
                )) +
                (rtd %*% matrix(
                    ifelse(
                        is.null(ncol(rtd)),
                        0:(length(rtd) - 1),
                        0:(ncol(rtd) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(rtd)),
                        length(rtd),
                        ncol(rtd)
                    )
                )) * 6
        )

        oneweek_pred <- data.frame(
            name = oneweek$name,
            team = oneweek$team,
            svm = oneweek_svm,
            ind = oneweek_ind
        )
    } else {
        oneweek_pred <- null
    }

    if (nrow(twoweek) > 0) {
        twoweek_svm <- predict(qb_svm2, newdata = twoweek)

        td <- predict(qb_td2, newdata = twoweek, 'probs')
        int <- predict(qb_int2, newdata = twoweek, 'probs')
        rtd <- predict(qb_rutd2, newdata = twoweek, 'probs')
        twoweek_ind <- (
            predict(qb_yds2, newdata = twoweek) / 25 +
                predict(qb_ruyds2, newdata = twoweek) / 10 +
                (td %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(td) - 1),
                        0:(ncol(td) - 1)
                    ),
                    nrow = ifelse(is.null(ncol(td)),
                                  length(td),
                                  ncol(td)
                    )
                )) * 4 -
                (int %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(int) - 1),
                        0:(ncol(int) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(td)),
                        length(int),
                        ncol(int)
                    )
                )) +
                (rtd %*% matrix(
                    ifelse(
                        is.null(ncol(rtd)),
                        0:(length(rtd) - 1),
                        0:(ncol(rtd) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(rtd)),
                        length(rtd),
                        ncol(rtd)
                    )
                )) * 6
        )

        twoweek_pred <- data.frame(
            name = twoweek$name,
            team = twoweek$team,
            svm = twoweek_svm,
            ind = twoweek_ind
        )
    } else {
        twoweek_pred <- null
    }

    if (nrow(threeweek) > 0) {
        threeweek_svm <- predict(qb_svm3, newdata = threeweek)

        td <- predict(qb_td3, newdata = threeweek, 'probs')
        int <- predict(qb_int3, newdata = threeweek, 'probs')
        rtd <- predict(qb_rutd3, newdata = threeweek, 'probs')
        threeweek_ind <- (
            predict(qb_yds3, newdata = threeweek) / 25 +
                predict(qb_ruyds3, newdata = threeweek) / 10 +
                (td %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(td) - 1),
                        0:(ncol(td) - 1)
                    ),
                    nrow = ifelse(is.null(ncol(td)),
                                  length(td),
                                  ncol(td)
                    )
                )) * 4 -
                (int %*% matrix(
                    ifelse(
                        is.null(ncol(td)),
                        0:(length(int) - 1),
                        0:(ncol(int) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(td)),
                        length(int),
                        ncol(int)
                    )
                )) +
                (rtd %*% matrix(
                    ifelse(
                        is.null(ncol(rtd)),
                        0:(length(rtd) - 1),
                        0:(ncol(rtd) - 1)
                    ),
                    nrow = ifelse(
                        is.null(ncol(rtd)),
                        length(rtd),
                        ncol(rtd)
                    )
                )) * 6
        )

        threeweek_pred <- data.frame(
            name = threeweek$name,
            team = threeweek$team,
            svm = threeweek_svm,
            ind = threeweek_ind
        )
    } else {
        threeweek_pred <- null
    }

    qb_pred <- rbind(oneweek_pred, twoweek_pred, threeweek_pred)
    qb_pred$name <- as.character(qb_pred$name)
    qb_pred$team <- as.character(qb_pred$team)

    price$position <- 'QB'
    qb_pred <- price %>%
        dplyr::select(
            name,
            position,
            salary
        ) %>%
        dplyr::inner_join(
            y = qb_pred,
            by = c('name')
        )

    return(qb_pred)
}