Oakland A’s general manager BILLY BEANE in 2002 used moneyball theory to pick a team of undervalued players that would go on to achieve a 20-game winning streak and clinch the American League West. AFTER losing three highly valuable playerto MARKET free agency.
MEASURES … “METRICS” …
“MORE” (production) … VALUE …
Using DATA ANALYTICS (METRICS” and moneyball theory, Beane hired the best players he could with an extremely limited budget for payroll.
“FACTORS” of PRODUCTION …
“ECONOMY” (stewardship-management) of “sport” … “VALUES” …
“FORMULAS” … “EQUATION” …
The SUM(?) = PARTS(?)
a “FORMULA[s]” … an “EQUATION“
With approximately $41 million in salary, the Oakland A’s ultimately competed with larger market teams such as the Yankees, who spent over $125 million in payroll during the 2002 baseball season.
Exactly HOW did they do it?
INNOVATION … (outside “the box”) … ALTERNATIVE …
FACTORS of PRODUCTION
Beane performed data mining on hundreds of individual players, ultimately identifying statistics that were highly predictive of how many runs a player would SCORE … RUNS
These statistics weren’t necessarily numbers that baseball scouts traditionally VALUED
Instead of competing for HIGH-PRICE HOME-RUN hitters with high batting averages, he sought LOWER-COST players with high ON-BASE percentages.
His theory was that players with a higher ON-BASE percentage would be more valuable than those with lower on-base percentage even when those with the lower percentage ultimately hit more home runs and were faster and even stronger.
He also encouraged players to focus on WALKS, thereby forcing pitchers to throw strikes to ensure an out.
HIT (and miss) “STRIKES”? … TAKE “BALLS”? …
Between 2000 to 2006, the Oakland A’s went on to average 95 WINS, capture four American League West titles, and make five playoff appearances.
Although baseball scouts and general managers initially scoffed at moneyball principals, they slowly began to realize the validity of the theory and sought to take advantage of it.
The Red Sox tried to hire Billy Beane but were unsuccessful. Instead, they hired BILL JAMES – the creator of SABERMETRICS on which moneyball theory is based – in an advisory capacity.
Over the years, moneyball theory has had a legacy in baseball, allowing teams with significantly lower budgets to choose players that would allow them to successfully compete with big-market teams such as the Red Sox and Yankees.
According to a 2013 article on MLB.com, “Moneyball has played a role in 15 of 30 teams getting into at least one postseason series – not a Wild Card Game, but a postseason series—the last three years.
Moneyball may also be why NINE franchises have won the World Series the LAST 13 seasons.”
LESSONS – Moneyball
Today, the story of Billy Beane and moneyball theory is famous – book Moneyball and the film of the same name. But according to Forbes, “What’s interesting is that as widely-familiar as the story is, it is almost as widely misunderstood.”
BEWARE HIDDEN MONOPOLIES
Analyzing data was nothing new to baseball in 2002. Data on baseball players has been available since the 1800s and data analytics used since the ’70s.
Beane’s strategy was ground-breaking is because he “had the courage to USE the insight gleaned from DATA ANALYTICS to drive the way he ran his business …
PRINCIPLES & PRACTICE
‘Moneyball’ succeeded not because of data analytics but because Beane, the leader who understood the analytics’ potential and changed the organization so it could deliver on that potential.”
THINKING “OUTSIDE the BOX”
Beane took advantage of making data science (empirical – observable – measurable) part of an organization’s DNA, but just as importantly, it highlights how a big idea about big data can translate to serious business GAINS-PRODUCTION
EXPANDING the BOX
MORE “METRICS” (formulas … equations)
WHAT YOU CAN (empirical) … CAN’T MEASURE (intangible)
LESSONS of MONEY BALL … it’s LIMITS …
a “NEW” FORMULA … REQUIRING “MORE” FORMULAS … “MODELS” of SUCCESS …
the “MORALITY” of “MORE”
ADAM SMITH … THIS “PROGRAM” … MULTIPLICITY … MORE BOOKS … MORE WRITERS … MORE READERS …
LOGIC vs IL-logical
SUM vs PARTS
“METRICS” – MAXIMUMS and MINIMUMS
FACTORS of PRODUCTION (offense – maximizing strengths” – ADD)
FACTORS of PREVENTION (defense – minimizing weaknesses – AVOID)
PRODUCTS … PROCESS …
e.g. OZZIE SMITH – .262 career BA – 2460 hits. 1257 runs. 580 SB (#22nd) 793 RBI. 19 SEASONS … 2002 Hall of Fame Inductee
A “RUN SAVED” is a “RUN EARNED” …
defense “saved” runs – .978 FLD% … 13 (in row) GOLD GLOVES (Vizquel – 11 total – Concepcion – 4 in row)
Ozzie Smith 8,375 career assists at shortstop, more than any shortstop in baseball history. handled 12,624 career chances at shortstop, more than any shortstop. turned 1,590 double plays at shortstop, more than any National League shortstop .
Was “The Wizard of Oz” is the greatest defensive shortstop in Major League history?
relative range factor sucks, but Ozzie Smith’s numbers deserve a second look.
According to range factor, he made almost 1 more play per game than an average SS.
This would translate into about 50 runs/season above an average defensive SS, which would be in line with the number of runs above an average hitter that Babe Ruth produced per season.
right fielder arms – preventing “extra bases”
TOTAL FOOTBALL INDEX
HOCKEY “PLUS-MINUS” … POSITIVE(s) – NEGATIVE(s) ...
PERSONALITY – INTELLIGENCE (“I.Q.s)
COLLECTIVE “CULTURE” (collaboration)
THOUGHT PROCESS – PRODUCTION
BASE-RUNNING – “SPEED” (foot and mind)