ANGLE #1: BET AGAINST ANY TEAM THAT LOST (SU) TO THE LOS ANGLES LAKERS
THE
PREVIOUS NIGHT
Theory: Every NBA team gets up for the Lakers, like no other team. Even
though the Lakers are struggling this season, there remains a mystique
associated with the three-time defending NBA champions. Teams get up
emotionally when playing the Lakers. Conventional wisdom suggests
betting
against teams that "upset" Los Angeles, because of an impending
"letdown"
factor. But the numbers show the better play is betting against teams
that
LOSE to Los Angeles, when playing the following night. When they lose
(SU)
the reaction is often devastating. It's very difficult to get back up
and go
to the next game after losing a game (either home or away) to the
champs.
This angle has been strong since the Lakers won their first of three
championships and should continue at least through the end of this
season.
SIDE NOTE: I'll eventually do some research and see if this applies to
the
"elite" teams of other sports. Right now, only the Detroit Red Wings
)NHL)
and Miami Hurricanes (Football) would probably qualify, since there are
no
elite teams in the other sports (exception: NYY in baseball -- but
baseball
has no emotional handicapping factors).
ANGLE #2: BET UNDER IN THE NEXT GAME WHEN THE FAVORITE IN THE PREVIOUS
GAME
SHOT AT LEAST 55 PERCENT FROM THE FIELD
Theory: This angle has produced a profit in every year it was tracked,
going
back so far as 1998. The idea is that everything went right for the
team
that shot 55> percent the previous game. Every roll went into the net,
most
of the three pointers fell, and the team may have even faced a bad (or
tired) defense. After a very good night of shooting, most teams fall
back to
average (around 43 percent shooting) in the next game. Furthermore, the
team
that shot 55> percent in the previous game was unlikely to be forced to
play
strong defense, since they won the game by outscoring the opponent
(it's
nearly 100 percent certain the team that shoots 55> percent will win
the
game SU). When the shooting percentages fall, there is a often a
greater
focus back on defense and the result is a game that goes UNDER the
total.
This trend is about 56 percent and has been a solid investment in the
first
half of the season.
ANGLE #3: BET AGAINST A TEAM THAT SHOT AT LEAST 10 PERCENT ABOVE ITS
SEASON
AVERAGE IN THE PREVIOUS GAME
Theory: This concept is related to the previous angle. When a team
shoots
the lights out in the previous game, it means just about everything
went
right for them. It's very difficult to maintain that kind of momentum
going
into the following game. When a team shoots 10> percent or better than
its
season average, that usually means 53> percent of all shots were
successful.
That may also mean that the key starters got extra minutes on the floor
and
could be fatigued in the next game. It could also mean the matchups in
the
previous game were extremely favorable to the good shooting team….which
will
usually NOT be the case in the next game. This is an angle based on the
concept of mean regression.
PART 2: Road Trips
I will define a "road trip" as any situation where a team plays THREE
consecutive games or more on the road. In the last three years, road
trips
for NBA teams have varied in length from 3 games up to 9 games (note:
In
2002, the Utah Jazz played nine straight games on the road during the
Winter
Olympics). Most road trips are 3 to 4 games in length. Each team
normally
plays about 3-4 "road trips" per season.
What initially interested me about investigating and eventually data
mining
road trips was the assumption that there "might" be some exploitable
factors, such as fatigue, which would create patterns of performance
reflected in ATS results. If identified and exploited, these patterns
could
be used to profit.
The natural assumption I, and many others have made -- is that the
longer a
team stays on the road, the more fatigued it gets. Hence, its level of
performance would be expected to decline. As my data will show, this is
NOT
the case.
In today's report, I shall convey some general statistics with regards
to
ALL ROAD TRIPS over the past three regular seasons. This data is from
seasons 1999-2999, 2000-2001, and 2001-2002. It does not include data
from
this current season. What follows are ATS results of every team during
the
course of its road trip:
ALL NBA TEAMS
3+ GAME ROAD TRIPS (ATS RESULTS)
1999-2002
GAME 1: 203-218 (48.2 percent wins)
GAME 2: 229-190 (54.8 percent wins)
GAME 3: 218-187 (53.9 percent wins)
GAME 4: 129-110 (53.2 percent wins)
GAME 5: 57-60 (47.4 percent wins)
GAME 6: 25-26 (49.5 percent wins)
GAME 7: 3-11 (22.6 percent wins)
GAME 8: 3-1 (75 percent wins)
GAME 9: 0-1 (0 percent wins)
From this data, I have drawn the following conclusions:
The most obvious discovery is dispelling the notion that long road
trips
hurt team (ATS) performance. Overall, teams on road trips covered the
spread
more often than not (about 52 percent of the time!).
Next, we see that there is little correlation to a team being on the
road
and a decline in performance. After Game 4, teams do not perform quite
as
well on the road as in the first four games -- going a collective
88-100 ATS
in Games 5-9. It appears linesmakers adjust the numbers and take the
road
trip into account, as these teams often get a more generous number of
points
as the road trip continues. The point is -- forget about notions of
GOING
AGAINST a team simply because it is playing its fifth or sixth straight
game
on the road. The teams are a combined 72-76, which is just about
break-even.
It's rare, but quite interesting to note that in Games 7-9 the road
team's
performance does decline significantly. These teams are just 6-13 ATS.
However, because these numbers are so small, I do not deem the results
to be
statistically significant.
It's interesting that in Game 2 of the road trip, the visitor covers
nearly
55 percent of the time! Based on over 400 trials, I believe there is
something relevant to this angle. My theory is this: By Game 2, teams
have
adjusted to the road trip and know that yet another road game will soon
follow. Perhaps they put more energy into Game 2 of a road series than
any
other. The ATS results and large number of trials appear to support
this
notion.
The previous argument is strengthened by the similar strong results of
Game
3. The visitor wins nearly 54 percent of the games. To break down some
of
the findings -- I noted in my research that teams on longer road rips
(4+
games) did much better in Games 2 and 3 than others who were playing
3-game
road trips. The teams playing 3 game road trips did not fare as well in
games 2 and 3. From this, we can conclude the road teams are more
focused in
the early part of the trip, knowing they will be on the road for a
(longer)
extended stretch.
The only "angle" which might be exploitable based on the naked data I
have
put forth is BETTING ON TEAMS IN GAME 2 OF ANY 3+ GAME ROAD TRIP. The
downside of this angle is that it is very marginal -- 54.8 percent
wins.
I'll leave it up to handicappers to decide for themselves if this
warrants a
wager or not. At the very least, this factor should be taken into
account if
you are considering a bet on the game where one of the teams falls into
this
category. I certainly would not wager AGAINST any team playing a second
road
game (of 3+). That translates into less than 43 percent covers (about 3
percent of NBA games PUSH).
PART 3: Situational Wagers Based on NBA Road Trips
In the previous segment, I posted raw data for all road trips over the
past
three seasons. Unfortunately, things are never so simple as just
playing on
or against a team based on how long it's been on the road. Were it only
that
easy!
What I hope to discover are specific situations where road teams
deviate
from the break-even range (47-53 percent) on road trips. In other
words, can
we identify situations where we can expect a road team to play well, or
poorly (based on the extended road trip)? Furthermore, we must also ask
ourselves -- are there money management systems that can be used to
profit
from these patterns of team performance? If so, is a Martingale
progressive
the best wagering strategy? I'll try to answer these questions, first
in
today's report and then in tomorrow's follow-up.
We all know that team sports are just as much about mental focus and
motivation, as physical talent and ability. To wit -- the "better" team
does
not always win! Let's look at a few angles where motivation may be the
primary factor in determining the outcome as it relates to wagering on
road
teams:
ANGLE #4: BET ON ANY ROAD TEAM IN GAME 2 (OF A 3+ ROAD SERIES),
PROVIDED
THAT THE TEAM LOST (ATS) IN GAME 1
Theory: Keep in mind that ALL road teams in Game 2 have covered 54.8
percent
of time. So, based on this angle alone -- we are ahead of the vig. Now,
let's qualify this broad angle and make it much stronger. A team that
is on
the road for 3+ games means the team will be away from home perhaps a
week,
or longer. The team is usually a dog in most road games. However, the
team
also knows the upcoming road string is a challenge and most athletes
give a
stronger effort when motivated. After a Game 1 loss, the last thing a
road
team wants is to go 0-2 (or worse) on the road trip and face the
possibility
of losing streak. Accordingly, the road team usually plays better in
Game 2,
when coming off an ATS loss in the first game. Note: This angle is
stronger
for SU losers of Game 1. When a team loses SU, it's obviously more of a
motivator than losing ATS. However, my data which follows concentrates
only
on ATS results.
Here is the data from 1999-2002 for ALL regular season games:
There were 218 losses in Game 1 road teams:
In Game 2, these teams went:
120 pointspread wins
92 pointspread losses
= 56.8 percent covers
(note: pushes were not counted)
CONCLUSION: We won't get rich of this system, but I'll take nearly 57
percent situational plays anytime I can get them.
2003 RESULTS: 1-0
ANGLE #5: BET ON TEAMS IN GAME 4 of a 4+ ROAD TRIP, PROVIDING THEY LOST
THE
LAST THREE PREVIOUS ROAD GAMES (ATS)
Theory: Keep in mind that ALL road teams in Game 4 have covered 53.2
percent
of time. So, based on this angle alone -- we are ahead of the vig. Now,
let's qualify this broad angle and make it stronger. Teams in the midst
of a
4-game road skid are in a slump. Bettors start to avoid these teams
like the
plague, which often translates into good line value from oddsmakers.
The
losing team certainly wants to stop the streak as soon as possible and
is
doubly motivated in the next road game. Also, there is usually less
pressure
to win on the road than back at home, which makes this road spot
particularly advantageous. This situation has come up only 25 times in
the
last three years, but the results have been exceptional:
Here is the data from 1999-2002 for ALL regular season games:
There were 25 situations of road teams on a 3+ game losing streak:
In Game 4, these teams went:
18 pointspread wins
7 pointspread losses
= 72 percent covers
(note: pushes were not counted)
CONCLUSION: Too bad this comes up so rarely. But this averages out to
about
8 plays per season and looks to be an excellent spot.
2003 RESULTS: 0-0
SIDE NOTE: Teams that lost the first two games (ATS) on a 3+ game road
trip
are just 44-42 (ATS) in Game 3. It's interesting that both the Game 2
and
Game 4 rebound-off-a-loss situation applies, but the results are much
weaker
in Game 3. I only bring this up so bettors will not fall into a trap
thinking that all of the road teams coming off losses are always worthy
of a
wager.
PART 4: Martingale (Progressive) Betting Strategies (EXPERIMENTAL)
Betting systems such as Martingales commonly lead to "gamblers ruin."
That
is, they are devastating to your bankroll and dangerous to you mental
health
if you employ them in casino gambling games. However, some
Martingale-based
systems are applicable to sports gambling. The reason why shall be
discussed
in this introduction.
The most common Martingale System is "doubling up." That means, after
each
loss, you bet the total amount of your losses in the sequence to date,
plus
one unit. For instance, after losing five bets in a row, we would bet
1+2+4+8+16 (+1) for a total of 32 units on the sixth bet. The trouble
with
employing Martingales in casino games is that it does not provide any
mathematical advantages to the gambler. It might seem "impossible" to
lose X
bets in a row, but the odds of it happening are certain and cannot be
overcome with creative doubling-up strategies. In short, you are only
prolonging the inevitable (the gambler's ruin).
However, in sports gambling Martingales can be a profitable money
management
strategy. This is because sports teams -- unlike dice or cards --
embody a
"human" element which causes greater resistance to deviations away from
the
statistical mean. For instance, the odds of a coin coming up heads
after 20
straight tails is still 50 percent on the 21st flip. But in the case of
sports teams, as one team goes on a long winning or losing streak, it
becomes more challenging with each and every game to continue the
repetition. This is because all players have emotions and physical
limitations, unlike coins or other gambling devices. Furthermore, over
time
-- the odds on the streaking team continue to move to the point where
the
team will no longer be able to cover the number. For instance, an NBA
team
that wins 15 games in a row will most certainly be a sizable favorite
over
any team it plays in Game 16 of the streak. Ultimately, the odds will
"catch
up" with the team and they will not be able to cover an inflated
number.
Conversely, for losing teams, oddsmakers will eventually give the bad
team
too many points and they will eventually cover the line.
EXAMPLE: In the last six seasons of college football, only one team has
gone
winless ATS (Tulsa, a few years ago). That's one team out of more than
600
trials. What happened was -- oddmakers gradually gave bad teams more
and
more points, until finally the team was able to cover the line.
Consider
that when the Houston Rockets lost 15 straight SU last season, they
covered
in four of those games and would have won on a progressive wagering
series.
What interests me is betting cycles where we wager either for or
against
teams on road trips. There are many deviations of Martingales, but I'll
keep
this simple and use the 1-2-4-8 etc. progression.
EXPERIMENTAL ANGLE #1: AFTER A ROAD TEAM LOSES GAME 1 OF A 4+ GAME ROAD
TRIP, BET A 1-2-4 PROGRESSIVE IN GAMES 2, 3, AND 4 UNTIL A COVER IS
ACHIEVED.
Theory: Note from previous data that Games 2, 3, and 4 produces 53+
percent
covers. It's exceptionally very rare for any road team to lose FOUR
consecutive ATS decisions. From 1999-2002 (three complete regular
seasons)
this occurred only 8 times. Let's see what happens if we were to bet a
1-2-4
progressive in every 4+ game road series -- provided the team lost its
first
road game ATS.
108 times you would earn 1 unit…..
+$10,800 (at $100 per unit)
83 times you would lose .1 unit (the vig on Game 2 and 3 losses)….
-$830.
8 times you would lose 7.7 units (applies to losing all four games of
the
series)….
-$6,160.
The net profit for this system is 38.1 units over the past three
seasons.
That translates into $3,810, or about $1,280, per season.
CONCLUSION: I stress this is a system that has produced marginal (but
indeed, positive) results. I will track this progressive system in a
separate category, which will NOT be included in the overall NBA
results.
2003 RESULTS: +/- 0 units
PART 5: This segment will focus on an NBA overtime angle. Handicapper
Jim
Barnes came up with this angle, which was published recently in one of
the
gambling periodcals.
ANGLE #6: BET ANY TEAM TO GO UNDER IN ITS NEXT GAME FOLLOWING AN
OVERTIME
GAME.
Theory: Teams that play overtime games often shoot poorly the next
game.
Perhaps the lack of intensity in the follow-up after a game where every
shot
counts creates a lack of focus and a lackluster performance
offensively. The
numbers in support of this theory are not earth-shattering, but do
suggest
there is something to this angle:
Over the past two seasons….
OVERTIME IN LAST GAME, NEXT GAME AT HOME:
82-66-4 in favor of UNDERS
OVERTIME IN LAST GAME, NEXT GAME ON ROAD:
85-67-0 in favor of UNDERS
COMBINED: 167-133-4 (56 percent)
2003 RESULTS: 3 -- 1 -- 0
PART 6: One common myth in NBA betting is to bet against a home team in
its
first game, after it has been on the road for an extended period. The
reasoning sounds logical. The home team is usually "fatigued" and now
has to
either lay points as the home favorite and/or its value is reduced
since the
team is now playing back home.
I decided to tack the results and found there was no validity to this
angle
whatsoever. In fact, there appears to be slight value to actually
betting ON
these teams back at home, after they have played FIVE or more straight
road
games. The results were close to break even following road trips of 3
and 4
games. But after 5 games, the results took a slight turn.
ANGLE #7: BET ON ANY TEAM IN ITS FIRST GAME BACK HOME AFTER A ROAD TRIP
(provided the road trip was 5+ games)
Theory: There's nothing spectacular here according to the last three
years
of data, just 51-41 ATS since 1999. But that's still a slight edge woth
noting and should debunk the myth of betting against these home teams.
PART 7: NBA HOMESTANDS
I will define a "homestand" as any situation where a team plays THREE
consecutive games or more at home. In the last three years, homestands
for
NBA teams have varied in length from 3 games up to 8 games. Most road
trips
are 3 games in sequence. Each team normally plays about 3-4
"homestands" per
season.
What initially interested me about investigating and eventually data
mining
homestands was the assumption that there "might" be some exploitable
factors
-- either positive or negative -- which would create patterns of
performance
reflected in ATS results. If identified and exploited, these patterns
could
be used to profit.
The natural assumption I, and many others have made -- is that the
longer a
team stays at home, the better its performance will be (largely because
there is no travel involved). Hence, its level of performance would be
expected to increase as the homestand continues. As my data will show,
this
is NOT the case. In fact, the opposite appears to be true.
In today's report, I shall convey some general statistics with regards
to
ALL HOMESTANDS over the past three regular seasons. This data is from
seasons 1999-2999, 2000-2001, and 2001-2002. It does not include data
from
this current season. What follows are ATS results of every team during
the
course of its homestand:
ALL NBA TEAMS
3+ GAME HOMESTANDS (ATS RESULTS)
1999-2002
GAME 1: 212-210 (50.1 percent wins)
GAME 2: 234-186 (54.7 percent wins)
GAME 3: 197-224 (46.3 percent wins)
GAME 4: 93-75 (57.1 percent wins)
GAME 5: 25-32 (43.1 percent wins)
GAME 6: 4-10 (31.7 percent wins)
GAME 7: 3-3 (50 percent wins)
GAME 8: 1-1 (50 percent wins)
From this data, I have drawn the following conclusions:
1. The most obvious discovery is dispelling the notion that long
homestands
improve team (ATS) performance. While home teams covered the spread
more
often than not (about 52 percent of the time in all games), the longer
the
team remained at home, the worse its performance deteriorated. Note the
awful results of Games 5 and 6, just 29-42 ATS.
2. What was most remarkable was the apparent "zig zag" effect of
homestands.
Note that in Game 2, home teams tend to play very well (nearly 55
percent
covers based on 450 trials!). Yet in the very next game (Game 3), the
level
of performance falls off significantly! I suspect that after the teams
play
well in the second game, knowing that yet another home game is to
follow,
the players lose some focus (perhaps partying too much or just becoming
too
content with the victory). How else to explain a EIGHT PERCENT DECLINE
between games 2 and 3?
3. Notice the same "zig zag" effect from Games 3 to 4 and Games 4 to 5.
There is a whopping TEN PERCENT INCREASE in covers between games 3 and
4.
Again, I suspect that when teams lose the third game of a homestand,
they
want to close out the sequence with a much stronger effort in the next
game.
57 percent covers in Game 4! This alone qualifies as a legitimate
betting
angle.
4. In the rare instances of teams staying at home longer than five
games,
the decline in performance is significant. Home teams are just 33-46
ATS in
games 5 through 8 of a homestand. Again, I suspect too many
distractions at
home and inflated lines creates good situations to back the visiting
team.
5. Note that in Game 2, the home team wins 54.7 percent of games. I
tried to
improve upon this percentage, thinking that if the team LOST the first
game
of the homestand, the team would play much better in Game 2. The
results of
this angle were marginal. Teams that lose Game 1 (ATS) were 114-86 in
Game
2. That's 56.7 percent winners, which barely qualifies according to the
criteria I employ with blind angles. Teams that covered in Game 1 were
100-99 in Game 2.
6. One angle that flopped was betting teams in Game 3 that lost the
first
two games of the homestand. These teams would be expected to do well at
home
after two consecutive disappointments. But the record showed otherwise;
just
38 wins and 42 losses in Game 3 when that situation arises.
7. A related angle to the previous one is betting AGAINST the home team
if
they have covered in the previous two games. It seems logical to expect
some
overconfidence and line inflation. However, the results were 44-46 for
the
home team, not quite strong enough to fade these teams in Game 3.
ANGLE #8: BET ON ANY HOME TEAM PLAYING ITS FOURTH CONSECUTIVE GAME AT
HOME.
Theory: 57 percent covers based on 168 trials. The fourth game of a
homestand is usually the final game and means the team will go on the
road
for a week or longer. Teams want to close out the homestand with a win,
especially if they have lost the previous game.
2003 RESULTS: 0 -- 0 -- 0
ANGLE #9: BET ON ANY HOME TEAM IN THE MIDST OF A HOMESTAND IN GAME 2,
PROVIDED THEY LOST GAME 1 (ATS)
Theory: This angle would seem to be stronger if the team lost SU,
rather
than ATS. But the numbers showed 56.7 percent winners, based on over
200
trials. The bounce back motivator is strong, especially for home teams
that
did not play as well as expected in the previous home game.
//////////////
ΤΩΡΑ ΤΟ ΑΝΑΚΑΛΥΨΑ ΑΥΤΟ
THE
PREVIOUS NIGHT
Theory: Every NBA team gets up for the Lakers, like no other team. Even
though the Lakers are struggling this season, there remains a mystique
associated with the three-time defending NBA champions. Teams get up
emotionally when playing the Lakers. Conventional wisdom suggests
betting
against teams that "upset" Los Angeles, because of an impending
"letdown"
factor. But the numbers show the better play is betting against teams
that
LOSE to Los Angeles, when playing the following night. When they lose
(SU)
the reaction is often devastating. It's very difficult to get back up
and go
to the next game after losing a game (either home or away) to the
champs.
This angle has been strong since the Lakers won their first of three
championships and should continue at least through the end of this
season.
SIDE NOTE: I'll eventually do some research and see if this applies to
the
"elite" teams of other sports. Right now, only the Detroit Red Wings
)NHL)
and Miami Hurricanes (Football) would probably qualify, since there are
no
elite teams in the other sports (exception: NYY in baseball -- but
baseball
has no emotional handicapping factors).
ANGLE #2: BET UNDER IN THE NEXT GAME WHEN THE FAVORITE IN THE PREVIOUS
GAME
SHOT AT LEAST 55 PERCENT FROM THE FIELD
Theory: This angle has produced a profit in every year it was tracked,
going
back so far as 1998. The idea is that everything went right for the
team
that shot 55> percent the previous game. Every roll went into the net,
most
of the three pointers fell, and the team may have even faced a bad (or
tired) defense. After a very good night of shooting, most teams fall
back to
average (around 43 percent shooting) in the next game. Furthermore, the
team
that shot 55> percent in the previous game was unlikely to be forced to
play
strong defense, since they won the game by outscoring the opponent
(it's
nearly 100 percent certain the team that shoots 55> percent will win
the
game SU). When the shooting percentages fall, there is a often a
greater
focus back on defense and the result is a game that goes UNDER the
total.
This trend is about 56 percent and has been a solid investment in the
first
half of the season.
ANGLE #3: BET AGAINST A TEAM THAT SHOT AT LEAST 10 PERCENT ABOVE ITS
SEASON
AVERAGE IN THE PREVIOUS GAME
Theory: This concept is related to the previous angle. When a team
shoots
the lights out in the previous game, it means just about everything
went
right for them. It's very difficult to maintain that kind of momentum
going
into the following game. When a team shoots 10> percent or better than
its
season average, that usually means 53> percent of all shots were
successful.
That may also mean that the key starters got extra minutes on the floor
and
could be fatigued in the next game. It could also mean the matchups in
the
previous game were extremely favorable to the good shooting team….which
will
usually NOT be the case in the next game. This is an angle based on the
concept of mean regression.
PART 2: Road Trips
I will define a "road trip" as any situation where a team plays THREE
consecutive games or more on the road. In the last three years, road
trips
for NBA teams have varied in length from 3 games up to 9 games (note:
In
2002, the Utah Jazz played nine straight games on the road during the
Winter
Olympics). Most road trips are 3 to 4 games in length. Each team
normally
plays about 3-4 "road trips" per season.
What initially interested me about investigating and eventually data
mining
road trips was the assumption that there "might" be some exploitable
factors, such as fatigue, which would create patterns of performance
reflected in ATS results. If identified and exploited, these patterns
could
be used to profit.
The natural assumption I, and many others have made -- is that the
longer a
team stays on the road, the more fatigued it gets. Hence, its level of
performance would be expected to decline. As my data will show, this is
NOT
the case.
In today's report, I shall convey some general statistics with regards
to
ALL ROAD TRIPS over the past three regular seasons. This data is from
seasons 1999-2999, 2000-2001, and 2001-2002. It does not include data
from
this current season. What follows are ATS results of every team during
the
course of its road trip:
ALL NBA TEAMS
3+ GAME ROAD TRIPS (ATS RESULTS)
1999-2002
GAME 1: 203-218 (48.2 percent wins)
GAME 2: 229-190 (54.8 percent wins)
GAME 3: 218-187 (53.9 percent wins)
GAME 4: 129-110 (53.2 percent wins)
GAME 5: 57-60 (47.4 percent wins)
GAME 6: 25-26 (49.5 percent wins)
GAME 7: 3-11 (22.6 percent wins)
GAME 8: 3-1 (75 percent wins)
GAME 9: 0-1 (0 percent wins)
From this data, I have drawn the following conclusions:
The most obvious discovery is dispelling the notion that long road
trips
hurt team (ATS) performance. Overall, teams on road trips covered the
spread
more often than not (about 52 percent of the time!).
Next, we see that there is little correlation to a team being on the
road
and a decline in performance. After Game 4, teams do not perform quite
as
well on the road as in the first four games -- going a collective
88-100 ATS
in Games 5-9. It appears linesmakers adjust the numbers and take the
road
trip into account, as these teams often get a more generous number of
points
as the road trip continues. The point is -- forget about notions of
GOING
AGAINST a team simply because it is playing its fifth or sixth straight
game
on the road. The teams are a combined 72-76, which is just about
break-even.
It's rare, but quite interesting to note that in Games 7-9 the road
team's
performance does decline significantly. These teams are just 6-13 ATS.
However, because these numbers are so small, I do not deem the results
to be
statistically significant.
It's interesting that in Game 2 of the road trip, the visitor covers
nearly
55 percent of the time! Based on over 400 trials, I believe there is
something relevant to this angle. My theory is this: By Game 2, teams
have
adjusted to the road trip and know that yet another road game will soon
follow. Perhaps they put more energy into Game 2 of a road series than
any
other. The ATS results and large number of trials appear to support
this
notion.
The previous argument is strengthened by the similar strong results of
Game
3. The visitor wins nearly 54 percent of the games. To break down some
of
the findings -- I noted in my research that teams on longer road rips
(4+
games) did much better in Games 2 and 3 than others who were playing
3-game
road trips. The teams playing 3 game road trips did not fare as well in
games 2 and 3. From this, we can conclude the road teams are more
focused in
the early part of the trip, knowing they will be on the road for a
(longer)
extended stretch.
The only "angle" which might be exploitable based on the naked data I
have
put forth is BETTING ON TEAMS IN GAME 2 OF ANY 3+ GAME ROAD TRIP. The
downside of this angle is that it is very marginal -- 54.8 percent
wins.
I'll leave it up to handicappers to decide for themselves if this
warrants a
wager or not. At the very least, this factor should be taken into
account if
you are considering a bet on the game where one of the teams falls into
this
category. I certainly would not wager AGAINST any team playing a second
road
game (of 3+). That translates into less than 43 percent covers (about 3
percent of NBA games PUSH).
PART 3: Situational Wagers Based on NBA Road Trips
In the previous segment, I posted raw data for all road trips over the
past
three seasons. Unfortunately, things are never so simple as just
playing on
or against a team based on how long it's been on the road. Were it only
that
easy!
What I hope to discover are specific situations where road teams
deviate
from the break-even range (47-53 percent) on road trips. In other
words, can
we identify situations where we can expect a road team to play well, or
poorly (based on the extended road trip)? Furthermore, we must also ask
ourselves -- are there money management systems that can be used to
profit
from these patterns of team performance? If so, is a Martingale
progressive
the best wagering strategy? I'll try to answer these questions, first
in
today's report and then in tomorrow's follow-up.
We all know that team sports are just as much about mental focus and
motivation, as physical talent and ability. To wit -- the "better" team
does
not always win! Let's look at a few angles where motivation may be the
primary factor in determining the outcome as it relates to wagering on
road
teams:
ANGLE #4: BET ON ANY ROAD TEAM IN GAME 2 (OF A 3+ ROAD SERIES),
PROVIDED
THAT THE TEAM LOST (ATS) IN GAME 1
Theory: Keep in mind that ALL road teams in Game 2 have covered 54.8
percent
of time. So, based on this angle alone -- we are ahead of the vig. Now,
let's qualify this broad angle and make it much stronger. A team that
is on
the road for 3+ games means the team will be away from home perhaps a
week,
or longer. The team is usually a dog in most road games. However, the
team
also knows the upcoming road string is a challenge and most athletes
give a
stronger effort when motivated. After a Game 1 loss, the last thing a
road
team wants is to go 0-2 (or worse) on the road trip and face the
possibility
of losing streak. Accordingly, the road team usually plays better in
Game 2,
when coming off an ATS loss in the first game. Note: This angle is
stronger
for SU losers of Game 1. When a team loses SU, it's obviously more of a
motivator than losing ATS. However, my data which follows concentrates
only
on ATS results.
Here is the data from 1999-2002 for ALL regular season games:
There were 218 losses in Game 1 road teams:
In Game 2, these teams went:
120 pointspread wins
92 pointspread losses
= 56.8 percent covers
(note: pushes were not counted)
CONCLUSION: We won't get rich of this system, but I'll take nearly 57
percent situational plays anytime I can get them.
2003 RESULTS: 1-0
ANGLE #5: BET ON TEAMS IN GAME 4 of a 4+ ROAD TRIP, PROVIDING THEY LOST
THE
LAST THREE PREVIOUS ROAD GAMES (ATS)
Theory: Keep in mind that ALL road teams in Game 4 have covered 53.2
percent
of time. So, based on this angle alone -- we are ahead of the vig. Now,
let's qualify this broad angle and make it stronger. Teams in the midst
of a
4-game road skid are in a slump. Bettors start to avoid these teams
like the
plague, which often translates into good line value from oddsmakers.
The
losing team certainly wants to stop the streak as soon as possible and
is
doubly motivated in the next road game. Also, there is usually less
pressure
to win on the road than back at home, which makes this road spot
particularly advantageous. This situation has come up only 25 times in
the
last three years, but the results have been exceptional:
Here is the data from 1999-2002 for ALL regular season games:
There were 25 situations of road teams on a 3+ game losing streak:
In Game 4, these teams went:
18 pointspread wins
7 pointspread losses
= 72 percent covers
(note: pushes were not counted)
CONCLUSION: Too bad this comes up so rarely. But this averages out to
about
8 plays per season and looks to be an excellent spot.
2003 RESULTS: 0-0
SIDE NOTE: Teams that lost the first two games (ATS) on a 3+ game road
trip
are just 44-42 (ATS) in Game 3. It's interesting that both the Game 2
and
Game 4 rebound-off-a-loss situation applies, but the results are much
weaker
in Game 3. I only bring this up so bettors will not fall into a trap
thinking that all of the road teams coming off losses are always worthy
of a
wager.
PART 4: Martingale (Progressive) Betting Strategies (EXPERIMENTAL)
Betting systems such as Martingales commonly lead to "gamblers ruin."
That
is, they are devastating to your bankroll and dangerous to you mental
health
if you employ them in casino gambling games. However, some
Martingale-based
systems are applicable to sports gambling. The reason why shall be
discussed
in this introduction.
The most common Martingale System is "doubling up." That means, after
each
loss, you bet the total amount of your losses in the sequence to date,
plus
one unit. For instance, after losing five bets in a row, we would bet
1+2+4+8+16 (+1) for a total of 32 units on the sixth bet. The trouble
with
employing Martingales in casino games is that it does not provide any
mathematical advantages to the gambler. It might seem "impossible" to
lose X
bets in a row, but the odds of it happening are certain and cannot be
overcome with creative doubling-up strategies. In short, you are only
prolonging the inevitable (the gambler's ruin).
However, in sports gambling Martingales can be a profitable money
management
strategy. This is because sports teams -- unlike dice or cards --
embody a
"human" element which causes greater resistance to deviations away from
the
statistical mean. For instance, the odds of a coin coming up heads
after 20
straight tails is still 50 percent on the 21st flip. But in the case of
sports teams, as one team goes on a long winning or losing streak, it
becomes more challenging with each and every game to continue the
repetition. This is because all players have emotions and physical
limitations, unlike coins or other gambling devices. Furthermore, over
time
-- the odds on the streaking team continue to move to the point where
the
team will no longer be able to cover the number. For instance, an NBA
team
that wins 15 games in a row will most certainly be a sizable favorite
over
any team it plays in Game 16 of the streak. Ultimately, the odds will
"catch
up" with the team and they will not be able to cover an inflated
number.
Conversely, for losing teams, oddsmakers will eventually give the bad
team
too many points and they will eventually cover the line.
EXAMPLE: In the last six seasons of college football, only one team has
gone
winless ATS (Tulsa, a few years ago). That's one team out of more than
600
trials. What happened was -- oddmakers gradually gave bad teams more
and
more points, until finally the team was able to cover the line.
Consider
that when the Houston Rockets lost 15 straight SU last season, they
covered
in four of those games and would have won on a progressive wagering
series.
What interests me is betting cycles where we wager either for or
against
teams on road trips. There are many deviations of Martingales, but I'll
keep
this simple and use the 1-2-4-8 etc. progression.
EXPERIMENTAL ANGLE #1: AFTER A ROAD TEAM LOSES GAME 1 OF A 4+ GAME ROAD
TRIP, BET A 1-2-4 PROGRESSIVE IN GAMES 2, 3, AND 4 UNTIL A COVER IS
ACHIEVED.
Theory: Note from previous data that Games 2, 3, and 4 produces 53+
percent
covers. It's exceptionally very rare for any road team to lose FOUR
consecutive ATS decisions. From 1999-2002 (three complete regular
seasons)
this occurred only 8 times. Let's see what happens if we were to bet a
1-2-4
progressive in every 4+ game road series -- provided the team lost its
first
road game ATS.
108 times you would earn 1 unit…..
+$10,800 (at $100 per unit)
83 times you would lose .1 unit (the vig on Game 2 and 3 losses)….
-$830.
8 times you would lose 7.7 units (applies to losing all four games of
the
series)….
-$6,160.
The net profit for this system is 38.1 units over the past three
seasons.
That translates into $3,810, or about $1,280, per season.
CONCLUSION: I stress this is a system that has produced marginal (but
indeed, positive) results. I will track this progressive system in a
separate category, which will NOT be included in the overall NBA
results.
2003 RESULTS: +/- 0 units
PART 5: This segment will focus on an NBA overtime angle. Handicapper
Jim
Barnes came up with this angle, which was published recently in one of
the
gambling periodcals.
ANGLE #6: BET ANY TEAM TO GO UNDER IN ITS NEXT GAME FOLLOWING AN
OVERTIME
GAME.
Theory: Teams that play overtime games often shoot poorly the next
game.
Perhaps the lack of intensity in the follow-up after a game where every
shot
counts creates a lack of focus and a lackluster performance
offensively. The
numbers in support of this theory are not earth-shattering, but do
suggest
there is something to this angle:
Over the past two seasons….
OVERTIME IN LAST GAME, NEXT GAME AT HOME:
82-66-4 in favor of UNDERS
OVERTIME IN LAST GAME, NEXT GAME ON ROAD:
85-67-0 in favor of UNDERS
COMBINED: 167-133-4 (56 percent)
2003 RESULTS: 3 -- 1 -- 0
PART 6: One common myth in NBA betting is to bet against a home team in
its
first game, after it has been on the road for an extended period. The
reasoning sounds logical. The home team is usually "fatigued" and now
has to
either lay points as the home favorite and/or its value is reduced
since the
team is now playing back home.
I decided to tack the results and found there was no validity to this
angle
whatsoever. In fact, there appears to be slight value to actually
betting ON
these teams back at home, after they have played FIVE or more straight
road
games. The results were close to break even following road trips of 3
and 4
games. But after 5 games, the results took a slight turn.
ANGLE #7: BET ON ANY TEAM IN ITS FIRST GAME BACK HOME AFTER A ROAD TRIP
(provided the road trip was 5+ games)
Theory: There's nothing spectacular here according to the last three
years
of data, just 51-41 ATS since 1999. But that's still a slight edge woth
noting and should debunk the myth of betting against these home teams.
PART 7: NBA HOMESTANDS
I will define a "homestand" as any situation where a team plays THREE
consecutive games or more at home. In the last three years, homestands
for
NBA teams have varied in length from 3 games up to 8 games. Most road
trips
are 3 games in sequence. Each team normally plays about 3-4
"homestands" per
season.
What initially interested me about investigating and eventually data
mining
homestands was the assumption that there "might" be some exploitable
factors
-- either positive or negative -- which would create patterns of
performance
reflected in ATS results. If identified and exploited, these patterns
could
be used to profit.
The natural assumption I, and many others have made -- is that the
longer a
team stays at home, the better its performance will be (largely because
there is no travel involved). Hence, its level of performance would be
expected to increase as the homestand continues. As my data will show,
this
is NOT the case. In fact, the opposite appears to be true.
In today's report, I shall convey some general statistics with regards
to
ALL HOMESTANDS over the past three regular seasons. This data is from
seasons 1999-2999, 2000-2001, and 2001-2002. It does not include data
from
this current season. What follows are ATS results of every team during
the
course of its homestand:
ALL NBA TEAMS
3+ GAME HOMESTANDS (ATS RESULTS)
1999-2002
GAME 1: 212-210 (50.1 percent wins)
GAME 2: 234-186 (54.7 percent wins)
GAME 3: 197-224 (46.3 percent wins)
GAME 4: 93-75 (57.1 percent wins)
GAME 5: 25-32 (43.1 percent wins)
GAME 6: 4-10 (31.7 percent wins)
GAME 7: 3-3 (50 percent wins)
GAME 8: 1-1 (50 percent wins)
From this data, I have drawn the following conclusions:
1. The most obvious discovery is dispelling the notion that long
homestands
improve team (ATS) performance. While home teams covered the spread
more
often than not (about 52 percent of the time in all games), the longer
the
team remained at home, the worse its performance deteriorated. Note the
awful results of Games 5 and 6, just 29-42 ATS.
2. What was most remarkable was the apparent "zig zag" effect of
homestands.
Note that in Game 2, home teams tend to play very well (nearly 55
percent
covers based on 450 trials!). Yet in the very next game (Game 3), the
level
of performance falls off significantly! I suspect that after the teams
play
well in the second game, knowing that yet another home game is to
follow,
the players lose some focus (perhaps partying too much or just becoming
too
content with the victory). How else to explain a EIGHT PERCENT DECLINE
between games 2 and 3?
3. Notice the same "zig zag" effect from Games 3 to 4 and Games 4 to 5.
There is a whopping TEN PERCENT INCREASE in covers between games 3 and
4.
Again, I suspect that when teams lose the third game of a homestand,
they
want to close out the sequence with a much stronger effort in the next
game.
57 percent covers in Game 4! This alone qualifies as a legitimate
betting
angle.
4. In the rare instances of teams staying at home longer than five
games,
the decline in performance is significant. Home teams are just 33-46
ATS in
games 5 through 8 of a homestand. Again, I suspect too many
distractions at
home and inflated lines creates good situations to back the visiting
team.
5. Note that in Game 2, the home team wins 54.7 percent of games. I
tried to
improve upon this percentage, thinking that if the team LOST the first
game
of the homestand, the team would play much better in Game 2. The
results of
this angle were marginal. Teams that lose Game 1 (ATS) were 114-86 in
Game
2. That's 56.7 percent winners, which barely qualifies according to the
criteria I employ with blind angles. Teams that covered in Game 1 were
100-99 in Game 2.
6. One angle that flopped was betting teams in Game 3 that lost the
first
two games of the homestand. These teams would be expected to do well at
home
after two consecutive disappointments. But the record showed otherwise;
just
38 wins and 42 losses in Game 3 when that situation arises.
7. A related angle to the previous one is betting AGAINST the home team
if
they have covered in the previous two games. It seems logical to expect
some
overconfidence and line inflation. However, the results were 44-46 for
the
home team, not quite strong enough to fade these teams in Game 3.
ANGLE #8: BET ON ANY HOME TEAM PLAYING ITS FOURTH CONSECUTIVE GAME AT
HOME.
Theory: 57 percent covers based on 168 trials. The fourth game of a
homestand is usually the final game and means the team will go on the
road
for a week or longer. Teams want to close out the homestand with a win,
especially if they have lost the previous game.
2003 RESULTS: 0 -- 0 -- 0
ANGLE #9: BET ON ANY HOME TEAM IN THE MIDST OF A HOMESTAND IN GAME 2,
PROVIDED THEY LOST GAME 1 (ATS)
Theory: This angle would seem to be stronger if the team lost SU,
rather
than ATS. But the numbers showed 56.7 percent winners, based on over
200
trials. The bounce back motivator is strong, especially for home teams
that
did not play as well as expected in the previous home game.
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ΤΩΡΑ ΤΟ ΑΝΑΚΑΛΥΨΑ ΑΥΤΟ
