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Breaking biases:
probably the best
strategy to improve
your player
recruitment
As humans, we naturally have biases. While they can provide shortcuts
to understand the world, biases can also lead to errors in
decision-making.
Actively acknowledging and overcoming biases improves the accuracy
of player selection, increasing the chances of making better recruiting
decisions.
The key to better scouting isn't just about adopting specific tools or
hiring more skilled scouts; it's about recognizing and overcoming
biases when assessing player qualities.
Actively acknowledging and overcoming biases improves the
accuracy of player selection, increasing the chances of making
better recruiting decisions.
We've identified ten specific biases that frequently emerge
within scouting teams.
Each bias represents a specific cognitive tendency or pattern
of thinking that can lead to errors in judgment or
decision-making.
10 specific examples
Common biases in player recruitment
● Definition: The tendency to favor information
confirming existing preconceptions.
● Example: If a scout once said a player is very
suitable for a club, they tend to oversee evidence
that proves them wrong.
Confirmation bias
#1
● Definition: Relying too heavily on the first piece of
information received.
● Example: A scout heard from a colleague that a
player is followed by a bigger club. When the scout
evaluates the player, they tend to overrate him.
#2
Anchoring bias
● Definition: Giving more weight to recent
performances.
● Example: A scout overestimates the importance of
the last performance evaluation of a player and
underestimates the importance of previous ones.
Recency bias
#3
● Definition: Generalizing a player's positive traits
across all aspects.
● Example: If a player showcases exceptional set
piece delivery, there might be an assumption that
they are also very good in delivering crosses in open
play, without seeing evidence for it when evaluating
him.
#4
Halo effect
● Definition: Preferring players who resemble
previous successful ones.
● Example: A club may favor a new striker mainly
because their style or appearance mirrors a
previously successful striker, even though there are
definite differences that could turn out less
positively.
Similarity bias
#5
● Definition: Overestimating one’s own ability to
predict a player's future success.
● Example: A scout or decision maker proclaims a
player would definitely become a success at their
club, disregarding the unpredictable nature of player
fit and development.
#6
Overconfidence bias
● Definition: Being overly optimistic about a player's
potential, ignoring warning signs.
● Example: A club might ignore a player's consistent
poor form, hoping that their past success will
resurface without addressing underlying issues.
Optimism bias
#7
● Definition: The absence of a representative sample
to draw conclusions on.
● Example: A scout is positive about a player based
on watching three matches, even though they were all
played at home against weaker teams.
#8
Selection bias
● Definition: Underestimating variance in outcomes if
an opinion is based on a small sample size.
● Example: A scout only watched a player in only one
match, but is convinced he is the ideal signing for
the club.
Sample size bias
#9
● Definition: Underestimating the contextual factors
that influence performances or outcomes.
● Example: A scout writes a negative report about a
player, but doesn’t assign enough weight to
contextual factors, like the bad pitch conditions, the
team’s tactics or the injury he just recovered from.
#10
Contextual influence bias
1. Confirmation bias: The tendency to favor information confirming existing preconceptions.
2. Anchoring bias: Relying too heavily on the first piece of information received
3. Recency bias: Giving more weight to recent performances.
4. Halo effect: Generalizing a player's positive traits across all aspects.
5. Similarity bias: Preferring players who resemble previous successful ones.
6. Overconfidence bias: Overestimating one’s own ability to predict the future.
7. Optimism bias: Being overly optimistic, ignoring warning signs.
8. Selection bias: The absence of a representative sample to draw conclusions on.
9. Sample size bias: Underestimating variance if an opinion is based on a small sample size.
10. Contextual influence bias: Underestimating the contextual factors that influence
performances.
10 common biases in football scouting
Effective
remedies for
overcoming
biases in football
scouting
Implement continuous education initiatives to enhance
awareness of biases among scouting staff. Without
awareness, addressing biases becomes challenging.
Remedy #1
Awareness and education
Blind scouting process
Remedy #2
Within an organization, individuals often tend to mirror
each other's opinions, including scouts, sometimes
without realizing it.
To counteract this bias, it's beneficial not to exchange
opinions about players until everyone has evaluated them
independently.
Ensure that your scouting team comprises individuals
with diverse backgrounds, experiences, and perspectives.
By assembling a team with varied viewpoints, both
internally and externally, you can tap into a broader range
of insights and considerations during player evaluations.
Remedy #3
Diverse scouting teams
Gather external opinions
Remedy #4
It’s a good thing that people within an organization
discuss players on a regular basis. One downside is that,
to some extent, tunnel vision can develop.
By consulting an external party, with no pre-information
on players, a fresh and unbiased perspective on players
can either confirm or challenge the current beliefs about
players.
Ready to
receive
unbiased
player
evaluations?
Interested?
360scouting.com
Learn more about us and how we can help you
Scouting:
better,
smarter,
faster.

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Breaking biases: probably the best strategy to improve your player recruitment

  • 1. Breaking biases: probably the best strategy to improve your player recruitment
  • 2. As humans, we naturally have biases. While they can provide shortcuts to understand the world, biases can also lead to errors in decision-making. Actively acknowledging and overcoming biases improves the accuracy of player selection, increasing the chances of making better recruiting decisions.
  • 3. The key to better scouting isn't just about adopting specific tools or hiring more skilled scouts; it's about recognizing and overcoming biases when assessing player qualities. Actively acknowledging and overcoming biases improves the accuracy of player selection, increasing the chances of making better recruiting decisions.
  • 4.
  • 5. We've identified ten specific biases that frequently emerge within scouting teams. Each bias represents a specific cognitive tendency or pattern of thinking that can lead to errors in judgment or decision-making. 10 specific examples Common biases in player recruitment
  • 6. ● Definition: The tendency to favor information confirming existing preconceptions. ● Example: If a scout once said a player is very suitable for a club, they tend to oversee evidence that proves them wrong. Confirmation bias #1
  • 7. ● Definition: Relying too heavily on the first piece of information received. ● Example: A scout heard from a colleague that a player is followed by a bigger club. When the scout evaluates the player, they tend to overrate him. #2 Anchoring bias
  • 8. ● Definition: Giving more weight to recent performances. ● Example: A scout overestimates the importance of the last performance evaluation of a player and underestimates the importance of previous ones. Recency bias #3
  • 9. ● Definition: Generalizing a player's positive traits across all aspects. ● Example: If a player showcases exceptional set piece delivery, there might be an assumption that they are also very good in delivering crosses in open play, without seeing evidence for it when evaluating him. #4 Halo effect
  • 10. ● Definition: Preferring players who resemble previous successful ones. ● Example: A club may favor a new striker mainly because their style or appearance mirrors a previously successful striker, even though there are definite differences that could turn out less positively. Similarity bias #5
  • 11. ● Definition: Overestimating one’s own ability to predict a player's future success. ● Example: A scout or decision maker proclaims a player would definitely become a success at their club, disregarding the unpredictable nature of player fit and development. #6 Overconfidence bias
  • 12. ● Definition: Being overly optimistic about a player's potential, ignoring warning signs. ● Example: A club might ignore a player's consistent poor form, hoping that their past success will resurface without addressing underlying issues. Optimism bias #7
  • 13. ● Definition: The absence of a representative sample to draw conclusions on. ● Example: A scout is positive about a player based on watching three matches, even though they were all played at home against weaker teams. #8 Selection bias
  • 14. ● Definition: Underestimating variance in outcomes if an opinion is based on a small sample size. ● Example: A scout only watched a player in only one match, but is convinced he is the ideal signing for the club. Sample size bias #9
  • 15. ● Definition: Underestimating the contextual factors that influence performances or outcomes. ● Example: A scout writes a negative report about a player, but doesn’t assign enough weight to contextual factors, like the bad pitch conditions, the team’s tactics or the injury he just recovered from. #10 Contextual influence bias
  • 16. 1. Confirmation bias: The tendency to favor information confirming existing preconceptions. 2. Anchoring bias: Relying too heavily on the first piece of information received 3. Recency bias: Giving more weight to recent performances. 4. Halo effect: Generalizing a player's positive traits across all aspects. 5. Similarity bias: Preferring players who resemble previous successful ones. 6. Overconfidence bias: Overestimating one’s own ability to predict the future. 7. Optimism bias: Being overly optimistic, ignoring warning signs. 8. Selection bias: The absence of a representative sample to draw conclusions on. 9. Sample size bias: Underestimating variance if an opinion is based on a small sample size. 10. Contextual influence bias: Underestimating the contextual factors that influence performances. 10 common biases in football scouting
  • 18. Implement continuous education initiatives to enhance awareness of biases among scouting staff. Without awareness, addressing biases becomes challenging. Remedy #1 Awareness and education
  • 19. Blind scouting process Remedy #2 Within an organization, individuals often tend to mirror each other's opinions, including scouts, sometimes without realizing it. To counteract this bias, it's beneficial not to exchange opinions about players until everyone has evaluated them independently.
  • 20. Ensure that your scouting team comprises individuals with diverse backgrounds, experiences, and perspectives. By assembling a team with varied viewpoints, both internally and externally, you can tap into a broader range of insights and considerations during player evaluations. Remedy #3 Diverse scouting teams
  • 21. Gather external opinions Remedy #4 It’s a good thing that people within an organization discuss players on a regular basis. One downside is that, to some extent, tunnel vision can develop. By consulting an external party, with no pre-information on players, a fresh and unbiased perspective on players can either confirm or challenge the current beliefs about players.
  • 23. Interested? 360scouting.com Learn more about us and how we can help you