Monte carlo simulation of 2023 NFL draft first round based on PFF big board rankings and team needs.
Each player is defined by a struct
// Player struct
struct player {
string name; // player name
string pos; // position
int num; // PFF big board ranking
};And each team is defined by a struct
// Team struct
// Note that for teams with multiple picks there will be multiple of these in the array
struct team {
string name;
// array of csv positional team needs (per PFF)
// i.e [G,C,WR]
vector<string> needs;
// what percentage of the time will the team
// reach for a play who plays the position of need
float reach_prob;
};Teams will sometimes (based on probabilities you set with reach_prob) randomly reach for a player at a position of need. Quarterback needy teams will do this way more often. Python file outputs probability distribution of each player landing at each team. Example output for my team (Jaguars) with pick 23
Jaguars_23 : {'Zay Flowers': 0.348, 'Joey Porter Jr': 0.318, 'Deonte Banks': 0.159, 'Jaxon Smith-Njigba': 0.115, 'Andre Carter II': 0.029, 'Broderick Jones': 0.022, 'Myles Murphy': 0.005, 'Bryan Bresee': 0.004}