The movie presents Oakland in dire straits losing two All-Star players after the 2001 season having no hope for the following season. The general manager faces internal resistance on how to approach finding replacement players. The point of the story is that using analytics on-base percentage (OBP) was the primary criteria for identifying and signing those players.

The movie gives the viewer a sense that Oakland was a real underdog team going into 2002 with little hope after losing their star players - that movie-contrived status doesn't square with the facts.

A generation of baseball fans will cite how analytics with regards to OBP led this team against all odds to the playoffs and that no other team could replicate this since the strategy was no longer a market inefficiency.

This belief is an incorrect conclusion and has helped give analytics a false sense of importance.

Let's start with some relevant facts about Oakland's team during this time period.

The team's on-base percentage, league rank and win-loss totals for this time period:

1998 .338 #14 74-88

1999 .355 #6 87-75

2000 .360 #6 91-70

2001 .345 #5 102-60

2002 .339 #7 103-59 -€” Moneyball year

2003 .327 #21 96-66

2004 .343 #9 91-71

2005 .330 #14 88-74

2006 .340 #10 93-69

2007 .338 #10 76-86

Oakland was already a high OBP team and actually declined in the 2002 Moneyball season when they supposedly added players based on OBP.

Teams that make the playoffs often have a ‘window of opportunity' which is essentially a bell curve for a core group of players. Oakland's core peaked during the 2001/2002 seasons.

The movie downplays the fact that the team had plenty of talent staying with the team going into 2002, they just needed to add several replacement players -€” no different than any other team year-in-year-out.

In 2002, offensively they still had Tejada/Chavez/Dye for a combined 92 homers and pitching they had Hudson/Zito/Mulder at their peak combining for over 670 innings and 57 wins.

This team would likely have made the playoffs with any average MLB player replacing Giambi/Damon (94 wins would have been enough for the wild card spot).

The next point is that in 2003 the team OBP dropped to the lowest level in this ten-year window, yet they still won 96 games. The following year, OBP shot back up, yet they won five fewer games. Clearly wins are not tied to OBP.

So why was the 2002 season so successful after losing several All-Star hitters?

Pitching.

Oakland's Team ERA and league rank for this time period.

1998 4.18 #23

1999 4.69 #11

2000 4.58 #11

2001 3.59 #2

2002 3.68 #3 - Moneyball year

2003 3.63 #2

2004 4.17 #10

2005 3.69 #6

2006 4.21 #7

2007 4.28 #13

Success within a window of opportunity is more closely aligned with the pitchers, not hitters.

• Zito peaked in 2002, left after 2006.
• Mulder peaked in 2001-2003, left after 2004.
• Hudson peaked in 2002-2003, left after 2004.

Moneyball's real lesson should have been that analytics are helpful, just not predictive. Having a high OBP is and always will be a solid strategy, but it is not necessary to win ballgames.

In 2023, the top five teams in OBP reached the playoffs while three were below league average including Baltimore which won 101 games.

Playoff team with league rank

#1 Atlanta .344 (104 wins)

#2 LA Dodgers .340 (100 wins)

#3 Texas .337 (90 wins)

#4 Tampa Bay .331 (99 wins)

#5 Houston .331 (90 wins)

#8 Toronto .329 (89 wins)

#9 Philadelphia .327 (90 wins)

#12 Minnesota .326 (87 wins)

#14 Arizona .322 (84 wins)

#16 Baltimore .321 (101 wins)

#17 Milwaukee .319 (92 wins)

#19 Miami .316 (84 wins)

I did enjoy the movie, it just gave a false impression of the value of analytics.

Analytics should be part of the discussion, not the sole basis of a decision.