• Corpus ID: 6610977

Human Perception of Performance

@article{Pappalardo2017HumanPO,
  title={Human Perception of Performance},
  author={Luca Pappalardo and Paolo Cintia and Dino Pedreschi and Fosca Giannotti and A L Barabasi},
  journal={ArXiv},
  year={2017},
  volume={abs/1712.02224}
}
Humans are routinely asked to evaluate the performance of other individuals, separating success from failure and affecting outcomes from science to education and sports. Yet, in many contexts, the metrics driving the human evaluation process remain unclear. Here we analyse a massive dataset capturing players' evaluations by human judges to explore human perception of performance in soccer, the world's most popular sport. We use machine learning to design an artificial judge which accurately… 

Figures from this paper

Selection procedures in sports: Improving predictions of athletes’ future performance

TLDR
This paper compares the popular clinical method with the actuarial approach, and why the latter approach often leads to superior performance predictions, and discusses the "signs" and the “samples” approaches.

Comparing subjective and objective evaluations of player performance in Australian Rules football

TLDR
It is highlighted that a select few features account for a majority of the variance when explaining subjective ratings of player performance, and that these vary by player role.

PlayeRank: Data-driven Performance Evaluation and Player Ranking in Soccer via a Machine Learning Approach

TLDR
This paper designs and implements PlayeRank, a data-driven framework that offers a principled multi-dimensional and role-aware evaluation of the performance of soccer players and shows its flexibility and efficiency, which makes it worth to be used in the design of a scalable platform for soccer analytics.

PlayeRank: Multi-dimensional and role-aware rating of soccer player performance

TLDR
PlayeRank is designed and implemented, a data-driven framework that offers a principled multi-dimensional and role-aware evaluation of the performance of soccer players and is robust in agreeing with experts' evaluation of players, significantly improving the state of the art.

A public data set of spatio-temporal match events in soccer competitions

TLDR
The nature of team sports like soccer, halfway between the abstraction of a game and the reality of complex social systems, combined with the unique size and composition of this dataset, provide the ideal ground for tackling a wide range of data science problems.

UNPACKING THE SALES CROSS-FUNCTIONAL COLLABORATION: THE ROLE OF SOCIAL IDENTIFICATION AND ORGANIZATIONAL RECIPROCITY

Sales' cross-functional collaboration networks are essential to improve key performance results. Salespeople engage in cross-functional networks when be motivated to act as knowledge brokers, sharing

Helping Your Docker Images to Spread Based on Explainable Models

TLDR
A solution based on interpretable decision tree and regression trees for estimating the popularity of a given Docker image, and for understanding how to improve an image to increase its popularity is presented.

Explaining Successful Docker Images Using Pattern Mining Analysis

TLDR
This paper presents a frequent pattern mining-based approach for understanding how to improve an image to increase its popularity, and can provide valuable insights to Docker image providers, helping them to design more competitive software products.

Sports selection in martial arts based on the harmonic stability of results at competitions

The aim of the study: to develop a new approach to sports selection in martial arts based on the analysis of the harmonic stability of the results of fighters in competitions during a sports career.

References

SHOWING 1-10 OF 38 REFERENCES

Quantifying the relation between performance and success in soccer

TLDR
This study analyzes more than 6,000 games and 10 million events in six European leagues and finds that a team's position in a competition's final ranking is significantly related to its typical performance, as described by a set of technical features extracted from the soccer data.

Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights

TLDR
Though this metric is based entirely on passes, the derived player rankings are largely consistent with general perceptions of offensive ability, e.g., Messi and Ronaldo are near the top.

An Examination of Judge Reliability at a major U.S. Wine Competition*

Abstract Wine judge performance at a major wine competition has been analyzed from 2005 to 2008 using replicate samples. Each panel of four expert judges received a flight of 30 wines imbedded with

Predicting Sports Scoring Dynamics with Restoration and Anti-Persistence

TLDR
Novel interpretable generative models of within-game scoring that allow for dependence on lead size and on the last team to score are presented and applied to comprehensive within- game scoring data for four sports leagues over a ten-year period.

The harsh rule of the goals: Data-driven performance indicators for football teams

TLDR
A data-driven approach is proposed and it is shown that there is a large potential to boost the understanding of football team performance and that a complex systems' view on football data has the potential of revealing hidden patterns and behavior of superior quality.

Save the last dance for me: unwanted serial position effects in jury evaluations.

TLDR
It is proposed that, independent of the evaluation procedure, judges' initial impressions of sequentially appearing candidates may be formed step-by-step, yielding serial position effects.

A network-based approach to evaluate the performance of football teams

TLDR
This paper proposes a model based on the observation of players’ behavior on the pitch that model the game of a team as a network and extracts simple network measures, showing the value of the approach on predicting the outcomes of a long-running tournament such as Italian major league.

Forecasting in the NBA and other team sports: Network effects in action

TLDR
This work proposes two network-based models to predict the behavior of teams in sports leagues that are parameter-free, that is, they do not have a single parameter, and moreover are sport-agnostic: they can be applied directly to any team sports league.

Performance Evaluation and Intrinsic Motivation Processes: The Effects of Achievement Orientation and Rewards

When individuals freely engage in an activity for its own sake, their behavior is considered intrinsically motivated. In reality, however, very few behaviors occur in a social vacuum. Most people

Soccer: Is scoring goals a predictable Poissonian process?

TLDR
A uniquely defined function is derived which quantitatively predicts the expected average outcome of a soccer match in terms of the fitness of both teams, and can be generalized to different types of sports events.