name(A),
current oiSH%(B),
career oiSH%(C),
current/career oiSH%(D),
games played(E),
total points(F),
PP+SH points(G),
EV points(H),
EV points based on career oiSH%(I),
predicted PP+SH points(J),
predicted EV points per game(K),
predicted total points after 82 games(L)
Note that the table above is sorted by predicted total points in reverse order (column L).
We have taken the top 20 point producers as of December 25, 2018.
We start with the premise that oiSH% is a good predictor of EV point production over a period of time long enough to not be skewed by short-term fluctuations caused by hot streaks or slumps. For the purposes of this thread, we take the full 2018/19 season as such a period. We have used career oiSH% instead of another number, such as last 3 years, or last year's oiSH% simply to make this as unbiased an analysis as possible. Are we going to use every top 20 player's oiSH% from last year? Some have really stepped up their game lately. But once we choose to do so, we introduce a personal bias into the analysis since there is no objective way to decide which player's last season's stats are more indicative of predicting this year's performance and which player's career stats are better suited for the task. Hence, we have chosen to use every player's career oiSH%. It is worth noting that the career oiSH% does include this year's oiSH%, that is, it is completely up to the latest game played.
Undoubtedly, some, maybe many, of the top 20 players will have career oiSH% this year. By using every player's career oiSH%, though, we have put all the players in an even keel.
Regarding non-EV production (PP + SH points), I have not used oiSH%, since the available data for it only counts EV production, but have rather made the simple assumption, for lack of better data or a non-biased approach that came to mind, that players will continue producing for the rest of the season at their current rate.
current oiSH%(B),
career oiSH%(C),
current/career oiSH%(D),
games played(E),
total points(F),
PP+SH points(G),
EV points(H),
EV points based on career oiSH%(I),
predicted PP+SH points(J),
predicted EV points per game(K),
predicted total points after 82 games(L)
Note that the table above is sorted by predicted total points in reverse order (column L).
We have taken the top 20 point producers as of December 25, 2018.
We start with the premise that oiSH% is a good predictor of EV point production over a period of time long enough to not be skewed by short-term fluctuations caused by hot streaks or slumps. For the purposes of this thread, we take the full 2018/19 season as such a period. We have used career oiSH% instead of another number, such as last 3 years, or last year's oiSH% simply to make this as unbiased an analysis as possible. Are we going to use every top 20 player's oiSH% from last year? Some have really stepped up their game lately. But once we choose to do so, we introduce a personal bias into the analysis since there is no objective way to decide which player's last season's stats are more indicative of predicting this year's performance and which player's career stats are better suited for the task. Hence, we have chosen to use every player's career oiSH%. It is worth noting that the career oiSH% does include this year's oiSH%, that is, it is completely up to the latest game played.
Undoubtedly, some, maybe many, of the top 20 players will have career oiSH% this year. By using every player's career oiSH%, though, we have put all the players in an even keel.
Regarding non-EV production (PP + SH points), I have not used oiSH%, since the available data for it only counts EV production, but have rather made the simple assumption, for lack of better data or a non-biased approach that came to mind, that players will continue producing for the rest of the season at their current rate.
