Wins Over Average (Value Stat)

Introducing Wins Over Average or (WOA)

The idea behind WOA was to create a new statistic similar to offensive WAR with less bias. WAR is not ballpark or team neutral. WAR measures a players proficiency on offense, their base running success, and their defensive ability. These three measures are rolled up using many statistics in the fWAR equation and are typically given as a comparison to league average. WOA can be translated as the number of team wins in which a player contributes to in a season for their team.

When I state that WAR is not team neutral, I am referring to team strategy. For example, when referring to a players base running ability and success, all base runners are measured on their ability to move base to base and around the bases 90 feet at a time. What the statistic is missing is team strategy. Some teams put emphasis on moving runners over, some teams always attempt to take the extra base hit, some teams bunt more or less frequently than others (Such as the 2018 Toronto Blue Jays who have bunted in less than 1% of their At Bats). Immediately you may say that team base running strategy does not influence WAR enough for their to be an impact. The fastest players will steal and take the extra base, and the slower runners will never get the steal sign and rarely will receive a hit and run. Players with average speed are affected the most by team context.

Another flaw with WAR is that the statistic is given as a function of WINS over replacement, yet the function to calculate WAR is focused mainly on runs.

Although no statistic will every capture every element of the game, I have created a statistic to help encapsulate strength of schedule, defensive ability, base running. and does not use replacement level. The statistic also uses a league average parameter that helps to compare WOA across years and decades. Arguably WOA is more effective at comparing players in different eras than WAR because the success and talent of a replacement level player changes over time. Because of the Team and League elements in this model, this statistic highly represents a players production for their team. WOA incorporates a team and leagues true runs power, to help uncover how a single player contributes against his own team and the league.

WOA = (Defense+wRAA+Strength+Baserunning) / (League Runs/Team Wins)

Defense = ((Position Value x Games Played) /162) + Defense Metric

wRAA = Weighted Runs Above Average

Strength = (League Runs Scored/League Plate Appearances - Team Runs Scored/Team Plate Appearances) x Player Plate Appearances

Baserunning = I'll keep that as a secret for now

What you will find interesting, is that WOA captures when players have spectacular production in a game, but that production does not contribute towards his team winning the game. For example, when Scooter Gennett hit 4 home runs against the Cardinals in one game in 2018, his production skyrocketed. But after the Reds were already winning 8-0, the production did not contribute towards "more" winning. Not to be confused with Win Probability Added (WPA), WOA encapsulates the number of games a player contributed towards winning in a season. Player WOA will change even if they are demoted to the Minor Leagues. As the leagues Run Scoring Environment changes daily, it takes that affect into all players aggregated metrics.

IN THE WORKS!

Pitching Runs Saved

A metric used to identify if a pitcher has been above market average or below.