There's many stats out there. What are a few or a checklist of stats that truly help you feel confident in making an informed decision before placing your investment? Thank you.
There's many stats out there. What are a few or a checklist of stats that truly help you feel confident in making an informed decision before placing your investment? Thank you.
There's many stats out there. What are a few or a checklist of stats that truly help you feel confident in making an informed decision before placing your investment? Thank you.
1. Adjusted stats for SOS, situation, and personnel. If you are using non adjusted stats - they are useless.
Once you solve for #1, then things become much clearer.
1. Adjusted stats for SOS, situation, and personnel. If you are using non adjusted stats - they are useless.
Once you solve for #1, then things become much clearer.
Points gained / given is top of the list.
Yards gotten / given is a topper as well.
Rush, passing yards, and yards per rush and pass attempt.
3rd down conversion percentage , and percentage allowed, is highly correlated to game outcomes.
Points gained / given is top of the list.
Yards gotten / given is a topper as well.
Rush, passing yards, and yards per rush and pass attempt.
3rd down conversion percentage , and percentage allowed, is highly correlated to game outcomes.
Pure Points For PPF / Pure Points Against PPA
This is attained by reading play-by-play and removing Points of turnovers ( noise) etc
INT for TD / PR for TD / KOR for TD / etc..
Pure Points For PPF / Pure Points Against PPA
This is attained by reading play-by-play and removing Points of turnovers ( noise) etc
INT for TD / PR for TD / KOR for TD / etc..
Unadjusted stats, (including removing outliers, random unlikely events, and end of game kneel downs), will just get you exactly to where the books are.
Some ways to out-think the books with stats- noting injuries/likely rests, T/O margin (books often remove this stat from their line because it is too unlikely in any given game).
In fact, T/O margin is one of the best edges, because if you *know* who is gonna win the TOs, that is an easy way to figure out an expected 3 points.
Unadjusted stats, (including removing outliers, random unlikely events, and end of game kneel downs), will just get you exactly to where the books are.
Some ways to out-think the books with stats- noting injuries/likely rests, T/O margin (books often remove this stat from their line because it is too unlikely in any given game).
In fact, T/O margin is one of the best edges, because if you *know* who is gonna win the TOs, that is an easy way to figure out an expected 3 points.
According to Billy Walters latest book that someone posted the link to here a few days ago, here are the main factors he looks into in capping :
Relative strength or power of the competing teams, which establishes
strength differential on a neutral field. These relative power ratings will
change over the season and from end of season to the beginning of the next
season.
Each team’s previous performances.
Home field advantage, which could vary by each home and away team.
Individual values for each player on each team.
Presence of injuries or illnesses that affect a team’s relative power. Note that
injuries/illnesses will subtract from a team’s relative power. Not only do you
need to adjust based on players out for the week, but you also must adjust
based on active players who are playing with an injury.
Game factors such as weather, each team’s previous schedule (e.g., byes,
multiple away games in a row, etc.), travel distance/diffculty, stadium quirks,
and turf types.
Motivational factors such as revenge, rivalries, coaching changes, etc
According to Billy Walters latest book that someone posted the link to here a few days ago, here are the main factors he looks into in capping :
Relative strength or power of the competing teams, which establishes
strength differential on a neutral field. These relative power ratings will
change over the season and from end of season to the beginning of the next
season.
Each team’s previous performances.
Home field advantage, which could vary by each home and away team.
Individual values for each player on each team.
Presence of injuries or illnesses that affect a team’s relative power. Note that
injuries/illnesses will subtract from a team’s relative power. Not only do you
need to adjust based on players out for the week, but you also must adjust
based on active players who are playing with an injury.
Game factors such as weather, each team’s previous schedule (e.g., byes,
multiple away games in a row, etc.), travel distance/diffculty, stadium quirks,
and turf types.
Motivational factors such as revenge, rivalries, coaching changes, etc
Dallas was among the best best rushing teams (maybe #1) against the Pats who are the worst at defending it. That was the only stat 1 stat needed to know taking the Cowboys large. Not saying its that simple but doing constant research analyzing stats can tend to overcomplicate things and most times amounts to nothing but wasted time. Hope that helps
Dallas was among the best best rushing teams (maybe #1) against the Pats who are the worst at defending it. That was the only stat 1 stat needed to know taking the Cowboys large. Not saying its that simple but doing constant research analyzing stats can tend to overcomplicate things and most times amounts to nothing but wasted time. Hope that helps
I've thought about this type of thing for a long time... But not diligent enough to track it
An extreme example would be ncaa terrible one in D...but they are playing a service academy
I've thought about this type of thing for a long time... But not diligent enough to track it
An extreme example would be ncaa terrible one in D...but they are playing a service academy
Meant Best pass rushing teams.. Hate typing from my phone
Meant Best pass rushing teams.. Hate typing from my phone
@PeAceMaKer7690
Awesome. What's a way to handicap turnovers? Example: if Team A commits 3 turnovers in a game, does regression to the means benefit them the next game?
@PeAceMaKer7690
Awesome. What's a way to handicap turnovers? Example: if Team A commits 3 turnovers in a game, does regression to the means benefit them the next game?
@vanzack
SOS is definitely a key stat. Jets yesterday were #2 in SOS vs KC 27, according to Sagarin. It definitely plays a part in handicapping -in the sports I handicap.
@StLBluesHockey
I would look at every sport and ask yourself - what's key driver of that particular sport. For me - football is about moving the ball and stopping a team from moving the ball.
I look at sagarin's ranks of teams and his schedule strength of teams. I take my ego out of the equation and recognize as an individual even with some tools to help capture the data, I can't look at everything so I use the opening lines the oddsmakers put on a game (i prefer madduxsports.com) as they capture many of the things (i'm speculating - as I don't know for sure) like home away, travel, injuries if known for certain, etc etc. Then theirs nuances of each particular game, you need to delve into, basically the more you peel the onion back and can find similar numbers the better chance of that result repeating. How you collect it, organize it, and can make comparisons as quickly as possible helps to interpret the data to come up with a conclusion. Every week the numbers change so you must be abreast of the situation.
BOL to you.
@vanzack
SOS is definitely a key stat. Jets yesterday were #2 in SOS vs KC 27, according to Sagarin. It definitely plays a part in handicapping -in the sports I handicap.
@StLBluesHockey
I would look at every sport and ask yourself - what's key driver of that particular sport. For me - football is about moving the ball and stopping a team from moving the ball.
I look at sagarin's ranks of teams and his schedule strength of teams. I take my ego out of the equation and recognize as an individual even with some tools to help capture the data, I can't look at everything so I use the opening lines the oddsmakers put on a game (i prefer madduxsports.com) as they capture many of the things (i'm speculating - as I don't know for sure) like home away, travel, injuries if known for certain, etc etc. Then theirs nuances of each particular game, you need to delve into, basically the more you peel the onion back and can find similar numbers the better chance of that result repeating. How you collect it, organize it, and can make comparisons as quickly as possible helps to interpret the data to come up with a conclusion. Every week the numbers change so you must be abreast of the situation.
BOL to you.
best info is found in box score teams win games but lost in the game fade the fuck out of em
example team won 17- 10 covered - 3 but woops passing yards 160 loser 180 rushing yards 210 loser 240
maybe get away with it 2 or 3 games because the teams they beat were pathetic and multi injured then this 4-1 team meets up with a 3-2 team and gets crushed at home as - 3 chalk it there look at teams previous box scores
last night TOP Giants 36:00 Seattle only 24:00
best info is found in box score teams win games but lost in the game fade the fuck out of em
example team won 17- 10 covered - 3 but woops passing yards 160 loser 180 rushing yards 210 loser 240
maybe get away with it 2 or 3 games because the teams they beat were pathetic and multi injured then this 4-1 team meets up with a 3-2 team and gets crushed at home as - 3 chalk it there look at teams previous box scores
last night TOP Giants 36:00 Seattle only 24:00
The Pats are a top 10 team against the rush! Both this season, and last season. Looking stats up is better than making stats up.
The Pats are a top 10 team against the rush! Both this season, and last season. Looking stats up is better than making stats up.
imho: Being able to access and utilize large data bases to check for reoccurring patterns. Situational handicapping over years of samples is
my approach, This can be done by using SDQL protocol with the data base at killersports.com. Some rare situations are incorrectly handled by the linemakers and
this shows up in plain sight by the close examination. I posted one of these angles last week that had won 23 straight games (ATS) over the last 2 years. This
week that angle went 3-1 and was a fg from a 4-0 sweep. The protocol is a cumbersome learning experience but well worth the time.
imho: Being able to access and utilize large data bases to check for reoccurring patterns. Situational handicapping over years of samples is
my approach, This can be done by using SDQL protocol with the data base at killersports.com. Some rare situations are incorrectly handled by the linemakers and
this shows up in plain sight by the close examination. I posted one of these angles last week that had won 23 straight games (ATS) over the last 2 years. This
week that angle went 3-1 and was a fg from a 4-0 sweep. The protocol is a cumbersome learning experience but well worth the time.
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